DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The following FINAL Office Action is in response to Applicant’s communication filed 03/11/2026 regarding Application 18/339,618.
Status of Claim(s)
Claim(s) 22, 24, 27-28, 31-32, 40-42, 45-46, and 50-56 is/are currently pending and are rejected as follows.
Response to Arguments – 102 and 103 Rejection
Applicant’s arguments in regards to the previously applied 102 and 103 rejection are rendered moot in view of the amended prior art rejection below.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 22, 24, 28, 31-32, 40-42, 45-46, 50, and 54-56 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wykman (US 2018/0213731 Al) in view of Ries (US 2023/0214788 Al)
Claim(s) 22 –
Wykman discloses the following limitations:
a communicator receiving positional information of a lawn mower detected by a position sensor installed at the lawn mower and receiving condition information of a lawn detected by a condition sensor installed at the lawn mower; (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
and a processor analyzing the condition information per piece of the positional information based on information received by the communicator, the processor generating and outputting improvement information indicating a method for improvement of condition of the lawn per piece of the positional information, (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
wherein the positional information and the condition information are detected while the lawn mower is mowing the lawn. (Wykman: Paragraph 53, “As such, for example, watering (or some other task) may be commenced and the system 10 may employ the sensor network 30 in combination with operation of the robotic vehicle 15 to monitor the distribution of the water (or fertilizer, etc.). The sensor network 30 may be transported to different locations, or data may be collected at different locations by the robotic vehicle 15 and then be used to provide feedback via the application manager 40 to direct more or less watering (or other resource utilization) in certain areas.”; Paragraph 65, “If a sensor network 30 is employed, the sensor network 30 may include sensors related to positional determination (e.g., a GPS receiver, an accelerometer, a camera, an inertial measurement unit and/or the like). Thus, for example, positional determinations may be made using GPS, inertial navigation, optical flow, visual location (e.g., VSLAM) and/or other positioning techniques or combinations thereof. Accordingly, the sensors may be used, at least in part, for determining the location of the robotic mower 15 relative to boundaries or other points of interest (e.g., a starting point or other key features) of the parcel 200, or determining a position history or track of the robotic mower 15 over time. The sensors may also detect collision, tipping over, or various fault conditions. In some cases, the sensors may also or alternatively collect data regarding various measurable parameters (e.g., moisture, nutrient stress, weed infestations, pest infestations, etc.) associated with particular locations on the parcel 200.”; Paragraph 101, “Inertial navigation systems may suffer from integration drift over time. Accordingly, inertial navigation systems may require a periodic position correction, which may be accomplished by getting a position fix from another more accurate method or by fixing a position of the robotic mower 15 relative to a known location. For example, navigation conducted via the IMU 850 may be used for robotic mower 15 operation for a period of time, and then a correction may be inserted when a GPS fix is obtained on robotic mower position. As an example alternative, the IMU 850 determined position may be updated every time the robotic mower 15 returns to the charge station 540 (which may be assumed to be at a fixed location). In still other examples, known reference points may be disposed at one or more locations on the parcel 200 and the robotic mower 15 may get a fix relative to any of such known reference points when the opportunity presents itself. The IMU 850 determined position may then be updated with the more accurate fix information. In some embodiments, the GPS receiver 852 may be embodied as a real time kinematic (RTK)—GPS receiver. As such, the GPS receiver 852 may employ satellite based positioning in conjunction with GPS, GLONASS, Galileo, GNSS, and/or the like to enhance accuracy of the GPS receiver 852. In some cases, carrier-phase enhancement may be employed such that, for example, in addition to the information content of signals received, the phase of the carrier wave may be examined to provide real-time corrections that can enhance accuracy.”)
Wykman does not explicitly disclose the use of previous condition information to generate improvement information, however, in analogous art of property management and maintenance, Ries discloses the following:
wherein the processor generates and outputs the improvement information based on results of analysis of the condition information per piece of the positional information and based on a countermeasure database, and (Ries: Paragraph 38, “Additionally, the turf maintenance system 100 includes a turf maintenance analytics engine 132 that uses the data acquired from the above-identified systems and devices to identify areas for improving the quality and efficiency of a turf maintenance job. The turf maintenance analytics engine 132 uses historical data acquired for a given area within the turf site 10 as well as a current status of the given area to determine whether improvements in a turf maintenance job are needed, how to implement said improvements, and whether resources such as the maintenance personnel 14 and maintenance equipment 114 are being used efficiently for that given area. In certain embodiments, the turf maintenance analytics engine 132 identifies the best qualified maintenance person 14 and maintenance equipment 114 for performing a scheduled task for a given area within the turf site 10, or conversely, identifies the least qualified or least efficient maintenance person 14 and maintenance equipment 114. The historical data and current status of an area within the turf site 10 are acquired from the one or more turf devices 112 installed at the turf site 10, as well as one or more of the weather service system 104, the task management system 106, the asset tracking system 108, and the irrigation system 110.”)
wherein the processor generates subsequent improvement information for a same position or a close position based on improvement information presented in the past and subsequent condition information. (Ries: Paragraph 38, “Additionally, the turf maintenance system 100 includes a turf maintenance analytics engine 132 that uses the data acquired from the above-identified systems and devices to identify areas for improving the quality and efficiency of a turf maintenance job. The turf maintenance analytics engine 132 uses historical data acquired for a given area within the turf site 10 as well as a current status of the given area to determine whether improvements in a turf maintenance job are needed, how to implement said improvements, and whether resources such as the maintenance personnel 14 and maintenance equipment 114 are being used efficiently for that given area. In certain embodiments, the turf maintenance analytics engine 132 identifies the best qualified maintenance person 14 and maintenance equipment 114 for performing a scheduled task for a given area within the turf site 10, or conversely, identifies the least qualified or least efficient maintenance person 14 and maintenance equipment 114. The historical data and current status of an area within the turf site 10 are acquired from the one or more turf devices 112 installed at the turf site 10, as well as one or more of the weather service system 104, the task management system 106, the asset tracking system 108, and the irrigation system 110.”; Paragraph 116, “FIG. 5 is a schematic diagram of an example of the turf maintenance analytics engine 132 of FIG. 1. In certain embodiments, the turf maintenance analytics engine 132 shares components with the intelligent scheduler 130. The turf maintenance analytics engine 132 includes a turf site database 502 that stores data on the various areas and features within the turf site 10. In certain embodiments, the turf site database 502 is shared with the intelligent scheduler 130 such that the turf site databases 402, 502 are the same database utilized by both the turf maintenance analytics engine 132 and the intelligent scheduler 130 to perform their assigned functions. In certain embodiments, the turf site database 502 stores additional data such as the historical conditions of the various areas and features within the turf site 10.”; Paragraph 130, “In certain embodiments, the algorithms 512 can generate automated route mapping for improved efficiency. For example, an optimized route for mowing the turf site 10 can be determined by the algorithms 512 based on historical performance.”; Paragraph 130, “In further embodiments, the algorithms 512 can be used to identify problems (e.g., chemical sprayer went next to pond just before fish kill), or can be used for process validation to prove that steps were properly performed (e.g., chemical sprayer never went near the pond).”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management.")
Claim(s) 24 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman further discloses the following:
wherein the condition sensor detects condition of soil, grass, or weeds in the lawn, and wherein the processor outputs a required operation or a required substance as the improvement information with respect to the soil, the grass, or the weeds in the lawn. (Wykman: Paragraph 24, “Example embodiments may provide a comprehensive system for monitoring lawn conditions at any of what may potentially be a number of locations throughout a particular parcel, and performing tasks relative to those locations under the direction of a distributed application manager. In some cases, the tasks and/or monitoring may be accomplished with the assistance of a mobile asset such as a robotic vehicle. In this regard, for example, the system may utilize a communication network that gathers information on growing conditions and lawn wellness from sensor equipment for association of the information with the areas from which the information was gathered. The system may also employ processing circuitry to associate a set of optimal or desirable growing condition and lawn wellness parameters with the various areas. When the information is received describing growing conditions and lawn wellness of the various areas, the processing circuitry may compare the growing conditions and lawn wellness (i.e., current conditions) to the growing condition and lawn wellness parameters (i.e., desired conditions) to determine whether and to what extent corrective actions may be needed to improve growing conditions and lawn wellness. The processing circuitry may receive the information from and/or communicate instructions to, a robotic vehicle. The robotic vehicle may provide a very high degree of flexibility and capability into the system with respect to mechanisms by which power, communication, and task related services may be provided within the system. As mentioned above, the processing circuitry may be distributed between local and remote management components so that some aspects of lawn maintenance may utilize remote assets or at least incorporate information available from abroad, while other aspects can be managed locally.”; Paragraph 59, “In an example embodiment, the memory 114 may store (or the processor 112 may otherwise access) a database (e.g., a growing condition database). Such database may correlate certain plants to the corresponding growing conditions that are ideal or preferred for optimal growth. As described above, current conditions may be monitored by the sensor network 30 and compared to the information in the database to determine any corrective action to be taken via the task performance equipment 20. Reduced costs and reduced environmental impact may therefore be achieved while achieving more optimal growing conditions.”; Paragraph 75, “The robotic mower 15 may also include one or more functional components 700 that may be controlled by the control circuitry 12 or otherwise be operated in connection with the operation of the robotic mower 15. The functional components 700 may include a wheel assembly (or other mobility assembly components), one or more cutting blades and corresponding blade control components, and/or other such devices. In embodiments where the robotic vehicle is not a mower, the functional components 700 may include equipment for taking soil samples, operating valves, distributing water, fertilizer, seed, powder, pellets or chemicals, and/or other functional devices and/or components.”; Paragraph 94, “As indicated above, the robotic mower 15 may also be configured to utilize the sensor network 30 and modules described above to engage in other functions indicative of intelligent vehicle autonomy. In this regard, for example, different tasks may be defined relative to different zones or at different times. In some cases, the user may be enabled to see the map view on a device (e.g., the electronic device 42) and select zones, a scheduling menu, autonomous operation settings, or other interaction mechanisms to define tasks for certain zones at certain times. Instructions may be provided to mow at different times, at different heights, in specific patterns, or with selected frequency in each respective zone. Alternatively or additionally, in embodiments where a robotic vehicle other than the robotic mower 15 is employed for performing tasks on the parcel 200, the robotic vehicle can be configured to autonomously traverse the parcel 200 to check soil conditions, monitor the health of grass or other plants, direct the application of water, fertilizer, chemicals, etc., or engage in other programmed activities.”; Paragraph 95, “Accordingly, the robotic mower 15 (or other robotic vehicle) may be provided with the positioning module 780, the vegetation analyzer 770, and the mapping module 760 to process sensor data received from the sensor network 30 and/or the camera 95. The robotic mower 15 may therefore be capable of accurately determining its position and gathering information about its surroundings. With accurate position determining capabilities, and the ability to experience its surroundings with multiple sensors, the robotic mower 15 may be configurable to provide feedback, warnings, or even implement automatic functionality (e.g., watering and/or fertilizing the lawn) responsive to detection of lawn conditions. The robotic mower 15 may therefore be more capable of being programmed to perform autonomous activities of various kinds and the value proposition for owners and operators may be greatly enhanced.”)
Claim(s) 28 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman further discloses the following:
wherein the processor determines a disease affecting grass or a pest infesting the grass based on the condition information and outputs control information according to the disease or the pest as the improvement information based on results of determination. (Wykman: Paragraph 65, “If a sensor network 30 is employed, the sensor network 30 may include sensors related to positional determination (e.g., a GPS receiver, an accelerometer, a camera, an inertial measurement unit and/or the like). Thus, for example, positional determinations may be made using GPS, inertial navigation, optical flow, visual location (e.g., VSLAM) and/or other positioning techniques or combinations thereof. Accordingly, the sensors may be used, at least in part, for determining the location of the robotic mower 15 relative to boundaries or other points of interest (e.g., a starting point or other key features) of the parcel 200, or determining a position history or track of the robotic mower 15 over time. The sensors may also detect collision, tipping over, or various fault conditions. In some cases, the sensors may also or alternatively collect data regarding various measurable parameters (e.g., moisture, nutrient stress, weed infestations, pest infestations, etc.) associated with particular locations on the parcel 200.”; Paragraph 79, “The applications may include applications for controlling the robotic mower 15 relative to various operations including determining an accurate position of the robotic mower 15 (e.g., using one or more sensors of the positioning module 780). Alternatively or additionally, the applications may include applications for controlling the robotic mower 15 relative to various operations including determining lawn conditions via water stress, nutrient stress, weed infestations, and/or pest infestations (e.g., using one or more sensors of the vegetation analyzer 770). Alternatively or additionally, the applications may include applications for controlling the robotic mower 15 relative to various operations including mapping a parcel or operating the robotic mower 15 relative to a map (generated or provided) (e.g., using one or more sensors of the mapping module 760). Alternatively or additionally, the applications may include applications for controlling the camera 95 and/or processing image data gathered by the camera 95 to execute or facilitate execution of other applications that drive or enhance operation of the robotic mower 15 relative to various activities described herein.”; Paragraph 89, “In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn.”; Paragraph 94, “As indicated above, the robotic mower 15 may also be configured to utilize the sensor network 30 and modules described above to engage in other functions indicative of intelligent vehicle autonomy. In this regard, for example, different tasks may be defined relative to different zones or at different times. In some cases, the user may be enabled to see the map view on a device (e.g., the electronic device 42) and select zones, a scheduling menu, autonomous operation settings, or other interaction mechanisms to define tasks for certain zones at certain times. Instructions may be provided to mow at different times, at different heights, in specific patterns, or with selected frequency in each respective zone. Alternatively or additionally, in embodiments where a robotic vehicle other than the robotic mower 15 is employed for performing tasks on the parcel 200, the robotic vehicle can be configured to autonomously traverse the parcel 200 to check soil conditions, monitor the health of grass or other plants, direct the application of water, fertilizer, chemicals, etc., or engage in other programmed activities.”)
Claim(s) 31 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman further discloses the following:
wherein the processor outputs watering information or ventilation information appropriate for the lawn or grass as the improvement information based on the condition information. (Wykman: Paragraph 46, “In some embodiments, in addition to employing the fixed assets described above, one or more mobile assets may be employed. Within such a context, for example, a robotic mower or watering device may be used to facilitate collection of data and/or the execution of tasks. Although any mobile asset could be employed, an example embodiment will be described herein within the context of a robotic lawn mower or watering device acting as the robotic vehicle 15. As described above, the robotic vehicle 15 may work within a work area defined by a boundary wire or other method. In some cases, the robotic vehicle 15 may perform a task (e.g., grass cutting or lawn watering (e.g., via transport of a small (e.g., 5 mm or less) hose linked to a water source via a hose reel) over the parcel 200. The robotic vehicle 15 may be equipped with an RFID reader to read the RFID tag of one or more sensors and/or pieces of task performance equipment 20. In some cases, the robotic vehicle 15 may include a positioning module 780 that is capable of noting the location at which one or more RFID tags was read. Accordingly, the robotic vehicle 15 may be able to obtain geographic location information for mapping the location of assets. As such, the locations of devices in the system 10 may be learned.”; Paragraph 54, “In some cases, the robotic vehicle 15 may be controlled to ensure that synchronization or sequencing can occur relative to the tasks performed on the parcel 200. For example, mowing can be secured while watering occurs in a given zone, or mowing can be planned a specific given time after watering has been accomplished. Moreover, since in some cases the sensor network 30 can detect natural watering (e.g., rain) and irrigation efforts, the application manager 40 may be enabled to manage resource consumption to optimize water utilization based on prevailing weather conditions. For example, if a rain event is detected, watering may be postponed. In some cases, the magnitude of a rain event may also be detected so that watering postponement may be accomplished for a time that is proportional to the amount of rain received. In still further examples, if the network 50 enables the application manager 40 to obtain weather forecast information (e.g., from the internet), then watering may be postponed even if a rain event has not yet occurred (e.g., if the rain event is forecast to occur within a given time period of an otherwise scheduled or apparently needed watering event). Thus, for example, the application manager 40 may access weather information from sites associated with the location of the parcel 200, or the application manager 40 may be enabled to utilize a subscription to a weather service to obtain forecast information.”; Paragraph 60, “In some cases, the application manager 40 may take automated action to improve growing conditions by controlling watering, fertilizing, cutting, lighting or other activities based on a determination that current conditions are not optimal. However, in other situations, the application manager 40 may be configured to provide an alert or instructions locally or via a smart phone or other remote device, to instruct or otherwise inform the owner/operator that some changes to current conditions may be advisable. The specific actions recommended may be identified, or an alert to check certain conditions may be provided. Accordingly, a relatively robust system for control of lawn conditions may be provided in an automated fashion. The result may be deemed to operate as a “smart lawn” that provides efficient control to achieve optimal growing conditions.”; Paragraph 95, “Accordingly, the robotic mower 15 (or other robotic vehicle) may be provided with the positioning module 780, the vegetation analyzer 770, and the mapping module 760 to process sensor data received from the sensor network 30 and/or the camera 95. The robotic mower 15 may therefore be capable of accurately determining its position and gathering information about its surroundings. With accurate position determining capabilities, and the ability to experience its surroundings with multiple sensors, the robotic mower 15 may be configurable to provide feedback, warnings, or even implement automatic functionality (e.g., watering and/or fertilizing the lawn) responsive to detection of lawn conditions. The robotic mower 15 may therefore be more capable of being programmed to perform autonomous activities of various kinds and the value proposition for owners and operators may be greatly enhanced.”)
Claim(s) 32 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman further discloses the following:
wherein the processor generates and outputs the improvement information based on a season or a location of the lawn in addition to the condition information. (Wykman: Paragraph 93, “Lawn conditions may be defined on the map in any suitable form. In this regard, in some cases, the map data may be converted into a model or image of the parcel 200 that can be displayed to merely show lawn conditions in a rudimentary form, or animation, graphic overlays, icons and/or other techniques may be employed to generate a sophisticated map view that may be exported to devices with more capable displays (e.g., the electronic device 42), or that may be displayed on a display device of the robotic mower 15 itself.”; Paragraph 95, “Accordingly, the robotic mower 15 (or other robotic vehicle) may be provided with the positioning module 780, the vegetation analyzer 770, and the mapping module 760 to process sensor data received from the sensor network 30 and/or the camera 95. The robotic mower 15 may therefore be capable of accurately determining its position and gathering information about its surroundings. With accurate position determining capabilities, and the ability to experience its surroundings with multiple sensors, the robotic mower 15 may be configurable to provide feedback, warnings, or even implement automatic functionality (e.g., watering and/or fertilizing the lawn) responsive to detection of lawn conditions. The robotic mower 15 may therefore be more capable of being programmed to perform autonomous activities of various kinds and the value proposition for owners and operators may be greatly enhanced.”; Paragraph 104, “The grass detector 858 may be configured to detect grass using any of a variety of different detection methods related to the particular features that the grass detector 858 is configured to perceive. In this regard, the grass detector 858 may be configured to detect grass based on structural and configured components that able to perceive chlorophyll, specific colors, and/or structures that may be used to indicate grass.”; Paragraph 107, “If the grass detector 858 is instead configured to identify grass based on passively receiving image data and analyzing the image data for colors in the images to distinguish grass from other materials, if possible. In some cases, the camera 95 may be used to capture image data. The image data may include RGB values for various pixels in each image. The RGB values may be transformed into hue, saturation and value (HSV) parameters. A center hue and width may be defined, and saturation and value thresholds could be computed. A determination as to whether a particular area is grass may then be determined based on a comparison of saturation and value parameters to the thresholds. In some cases, the camera 95 may also capture NIR information and both RGB and NIR values can be analyzed for color based grass detection.”)
Claim(s) 40 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman further discloses the following:
wherein the lawn mower is autonomous, wherein the communicator receives the positional information from the position sensor that is used by the lawn mower to travel autonomously, and wherein the communicator receives the condition information from the condition sensor that is used by the lawn mower to detect its surroundings when travelling autonomously. (Wykman: Paragraph 94, “As indicated above, the robotic mower 15 may also be configured to utilize the sensor network 30 and modules described above to engage in other functions indicative of intelligent vehicle autonomy. In this regard, for example, different tasks may be defined relative to different zones or at different times. In some cases, the user may be enabled to see the map view on a device (e.g., the electronic device 42) and select zones, a scheduling menu, autonomous operation settings, or other interaction mechanisms to define tasks for certain zones at certain times. Instructions may be provided to mow at different times, at different heights, in specific patterns, or with selected frequency in each respective zone. Alternatively or additionally, in embodiments where a robotic vehicle other than the robotic mower 15 is employed for performing tasks on the parcel 200, the robotic vehicle can be configured to autonomously traverse the parcel 200 to check soil conditions, monitor the health of grass or other plants, direct the application of water, fertilizer, chemicals, etc., or engage in other programmed activities.”; Paragraph 95, “Accordingly, the robotic mower 15 (or other robotic vehicle) may be provided with the positioning module 780, the vegetation analyzer 770, and the mapping module 760 to process sensor data received from the sensor network 30 and/or the camera 95. The robotic mower 15 may therefore be capable of accurately determining its position and gathering information about its surroundings. With accurate position determining capabilities, and the ability to experience its surroundings with multiple sensors, the robotic mower 15 may be configurable to provide feedback, warnings, or even implement automatic functionality (e.g., watering and/or fertilizing the lawn) responsive to detection of lawn conditions. The robotic mower 15 may therefore be more capable of being programmed to perform autonomous activities of various kinds and the value proposition for owners and operators may be greatly enhanced.”)
Claim(s) 41 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman further discloses the following:
a lawn mower; a position sensor; a condition sensor; and a lawn management assistance system according to claim 22. (Wykman: Paragraph 33, “The device interface 120 may include one or more interface mechanisms for enabling communication with other devices via the network 50. In some cases, the device interface 120 may be any means such as a device or circuitry embodied in either hardware, or a combination of hardware and software that is configured to receive and/or transmit data from/to sensors of the sensor network 30 and devices of the task performance equipment 20 in communication with the processing circuitry 110 by virtue of the device interface 120 being capable of sending and receiving messages via the network 50. In some example embodiments, the device interface 120 may provide interfaces for communication of components internal to the system 10 with components external to the system 10. For example, in an embodiment in which the application manager 40 is embodied as a computer or a server, the device interface 120 may enable communication (e.g., via the internet or wireless communication methods) with a smart phone of the owner/operator. This communication may also occur via the network 50 (or via a sub-network of the network 50) in some cases. However, it should also be appreciated that the owner/operator may directly interact with the application manager 40 via the user interface 130.”; Paragraph 49, “Furthermore, in some embodiments, the robotic vehicle 15 itself may be used to power the sensor network 30 when the robotic vehicle 15 is proximate to the sensors. In this regard, similar to the operation of an RFID tag, the robotic vehicle 15 may radiate signals that can be used by sensors proximate thereto to take measurements and transmit data measured to the robotic vehicle 15. Thus, for example, inductive power provision may be accomplished to transfer power to remote assets within the system 10. Power transfer or communication in this manner can be accomplished at relatively low power levels due to the proximity of the robotic vehicle 15 to the sensors or other devices that are being powered and/or communicated with. In some cases, the robotic vehicle 15 may also provide power to one or more of the sensors or the task performance equipment 20. For example, the sensor network 30 and/or task performance equipment 20 may have batteries that may be rechargeable by the robotic vehicle 15 transferring power from its own batteries to the batteries of the one or more sensors/task performance equipment via inductive or wireless power transfer. Physical contact may be employed for such power transfers in some cases as well.”; Paragraph 61, “Embodiments of the present invention may therefore be practiced using an apparatus in connection with the system of FIGS. 1-4. In an example embodiment, a robotic vehicle 15 (e.g., a robotic mower, a mobile sensing device, a watering device and/or the like) is provided with a positioning module 780, a mapping module 760, a vegetation analyzer 770, and a sensor network 30. The positioning module 780 may be configured to utilize one or more sensors to determine a location of the robotic vehicle 15 and direct continued motion of the robotic vehicle 15. The mapping module 760 may be configured to map a parcel or operate the robotic vehicle 15 relative to a map. The vegetation analyzer 770 may be configured to utilize one or more sensors to measure lawn conditions. The sensor network 30 may be configured to collect data (e.g., plant stress). Other structures may also be provided, and other functions may also be performed as described in greater detail below.”; Paragraph 63, “FIG. 5 illustrates an example operating environment for a robotic mower 15 that may be employed in connection with an example embodiment. However, it should be appreciated that example embodiments may be employed on numerous other robotic vehicles, so the robotic mower 15 should be recognized as merely one example of such a vehicle. The robotic mower 15 may operate to cut grass on a parcel 200 (i.e., a lawn), the boundary 530 of which may be defined using one or more physical boundaries (e.g., a fence, wall, curb and/or the like), a boundary wire, programmed location based boundaries or combinations thereof. When the boundary 530 is a boundary wire, the boundary wire may emit electrical signals that are detectable by the robotic mower 15 to inform the robotic mower 15 when the boundary 530 of the parcel 200 has been reached. Several robotic vehicles (e.g., a robotic watering vehicle) may operate in similarly defined areas, but an example embodiment will be described herein in connection with a robotic mower 15. However, it should be appreciated that example embodiments are not limited to application only on robotic mowers. Instead, example embodiments may also be practiced in connection with other robotic vehicles that operate within bounded regions.”)
Claim(s) 42 –
Wykman discloses the following limitations:
receiving positional information of a lawn mower detected by a position sensor installed at the lawn mower; (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
receiving condition information of a lawn detected by a condition sensor installed at the lawn mower; and (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
using a processor, analyzing the condition information per piece of the positional information and generating and outputting improvement information indicating a method for improvement of condition of the lawn per piece of the positional information, (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
wherein the positional information and the condition information are detected while the lawn mower is mowing the lawn. (Wykman: Paragraph 53, “As such, for example, watering (or some other task) may be commenced and the system 10 may employ the sensor network 30 in combination with operation of the robotic vehicle 15 to monitor the distribution of the water (or fertilizer, etc.). The sensor network 30 may be transported to different locations, or data may be collected at different locations by the robotic vehicle 15 and then be used to provide feedback via the application manager 40 to direct more or less watering (or other resource utilization) in certain areas.”; Paragraph 65, “If a sensor network 30 is employed, the sensor network 30 may include sensors related to positional determination (e.g., a GPS receiver, an accelerometer, a camera, an inertial measurement unit and/or the like). Thus, for example, positional determinations may be made using GPS, inertial navigation, optical flow, visual location (e.g., VSLAM) and/or other positioning techniques or combinations thereof. Accordingly, the sensors may be used, at least in part, for determining the location of the robotic mower 15 relative to boundaries or other points of interest (e.g., a starting point or other key features) of the parcel 200, or determining a position history or track of the robotic mower 15 over time. The sensors may also detect collision, tipping over, or various fault conditions. In some cases, the sensors may also or alternatively collect data regarding various measurable parameters (e.g., moisture, nutrient stress, weed infestations, pest infestations, etc.) associated with particular locations on the parcel 200.”; Paragraph 101, “Inertial navigation systems may suffer from integration drift over time. Accordingly, inertial navigation systems may require a periodic position correction, which may be accomplished by getting a position fix from another more accurate method or by fixing a position of the robotic mower 15 relative to a known location. For example, navigation conducted via the IMU 850 may be used for robotic mower 15 operation for a period of time, and then a correction may be inserted when a GPS fix is obtained on robotic mower position. As an example alternative, the IMU 850 determined position may be updated every time the robotic mower 15 returns to the charge station 540 (which may be assumed to be at a fixed location). In still other examples, known reference points may be disposed at one or more locations on the parcel 200 and the robotic mower 15 may get a fix relative to any of such known reference points when the opportunity presents itself. The IMU 850 determined position may then be updated with the more accurate fix information. In some embodiments, the GPS receiver 852 may be embodied as a real time kinematic (RTK)—GPS receiver. As such, the GPS receiver 852 may employ satellite based positioning in conjunction with GPS, GLONASS, Galileo, GNSS, and/or the like to enhance accuracy of the GPS receiver 852. In some cases, carrier-phase enhancement may be employed such that, for example, in addition to the information content of signals received, the phase of the carrier wave may be examined to provide real-time corrections that can enhance accuracy.”)
Wykman does not explicitly disclose the use of previous condition information to generate improvement information, however, in analogous art of property management and maintenance, Ries discloses the following:
wherein the processor generates and outputs the improvement information based on results of analysis of the condition information per piece of the positional information and based on a countermeasure database, and (Ries: Paragraph 38, “Additionally, the turf maintenance system 100 includes a turf maintenance analytics engine 132 that uses the data acquired from the above-identified systems and devices to identify areas for improving the quality and efficiency of a turf maintenance job. The turf maintenance analytics engine 132 uses historical data acquired for a given area within the turf site 10 as well as a current status of the given area to determine whether improvements in a turf maintenance job are needed, how to implement said improvements, and whether resources such as the maintenance personnel 14 and maintenance equipment 114 are being used efficiently for that given area. In certain embodiments, the turf maintenance analytics engine 132 identifies the best qualified maintenance person 14 and maintenance equipment 114 for performing a scheduled task for a given area within the turf site 10, or conversely, identifies the least qualified or least efficient maintenance person 14 and maintenance equipment 114. The historical data and current status of an area within the turf site 10 are acquired from the one or more turf devices 112 installed at the turf site 10, as well as one or more of the weather service system 104, the task management system 106, the asset tracking system 108, and the irrigation system 110.”)
wherein the processor generates subsequent improvement information for a same position or a close position based on improvement information presented in the past and subsequent condition information. (Ries: Paragraph 38, “Additionally, the turf maintenance system 100 includes a turf maintenance analytics engine 132 that uses the data acquired from the above-identified systems and devices to identify areas for improving the quality and efficiency of a turf maintenance job. The turf maintenance analytics engine 132 uses historical data acquired for a given area within the turf site 10 as well as a current status of the given area to determine whether improvements in a turf maintenance job are needed, how to implement said improvements, and whether resources such as the maintenance personnel 14 and maintenance equipment 114 are being used efficiently for that given area. In certain embodiments, the turf maintenance analytics engine 132 identifies the best qualified maintenance person 14 and maintenance equipment 114 for performing a scheduled task for a given area within the turf site 10, or conversely, identifies the least qualified or least efficient maintenance person 14 and maintenance equipment 114. The historical data and current status of an area within the turf site 10 are acquired from the one or more turf devices 112 installed at the turf site 10, as well as one or more of the weather service system 104, the task management system 106, the asset tracking system 108, and the irrigation system 110.”; Paragraph 116, “FIG. 5 is a schematic diagram of an example of the turf maintenance analytics engine 132 of FIG. 1. In certain embodiments, the turf maintenance analytics engine 132 shares components with the intelligent scheduler 130. The turf maintenance analytics engine 132 includes a turf site database 502 that stores data on the various areas and features within the turf site 10. In certain embodiments, the turf site database 502 is shared with the intelligent scheduler 130 such that the turf site databases 402, 502 are the same database utilized by both the turf maintenance analytics engine 132 and the intelligent scheduler 130 to perform their assigned functions. In certain embodiments, the turf site database 502 stores additional data such as the historical conditions of the various areas and features within the turf site 10.”; Paragraph 130, “In certain embodiments, the algorithms 512 can generate automated route mapping for improved efficiency. For example, an optimized route for mowing the turf site 10 can be determined by the algorithms 512 based on historical performance.”; Paragraph 130, “In further embodiments, the algorithms 512 can be used to identify problems (e.g., chemical sprayer went next to pond just before fish kill), or can be used for process validation to prove that steps were properly performed (e.g., chemical sprayer never went near the pond).”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management.")
Claim(s) 50 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman does not explicitly disclose the following, however, in analogous art of property management and maintenance, Ries discloses the following:
wherein, for a target position, the processor generates subsequent improvement information based on condition information detected in the past, improvement information presented in the past, and subsequent condition information. (Ries: Paragraph 38, “Additionally, the turf maintenance system 100 includes a turf maintenance analytics engine 132 that uses the data acquired from the above-identified systems and devices to identify areas for improving the quality and efficiency of a turf maintenance job. The turf maintenance analytics engine 132 uses historical data acquired for a given area within the turf site 10 as well as a current status of the given area to determine whether improvements in a turf maintenance job are needed, how to implement said improvements, and whether resources such as the maintenance personnel 14 and maintenance equipment 114 are being used efficiently for that given area. In certain embodiments, the turf maintenance analytics engine 132 identifies the best qualified maintenance person 14 and maintenance equipment 114 for performing a scheduled task for a given area within the turf site 10, or conversely, identifies the least qualified or least efficient maintenance person 14 and maintenance equipment 114. The historical data and current status of an area within the turf site 10 are acquired from the one or more turf devices 112 installed at the turf site 10, as well as one or more of the weather service system 104, the task management system 106, the asset tracking system 108, and the irrigation system 110.”; Paragraph 71, “The maintenance interface 103 includes a messaging module 364 that enables the maintenance person 14 to receive messages from the site supervisor 12. In certain embodiments, the messaging module 364 enables the maintenance person 14 to send messages to the site supervisor 12 such as to convey information relating to the conditions of a given area within the turf site 10 such as observations by the maintenance person 14 that are not identifiable from the data acquired from the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112. For example, the maintenance person 14 can identify a condition of an area on the turf site 10 that requires attention such as a diseased tree, a dead spot, downed tree branch, and the like. Thus, the messaging module 364 can enhance the collection of relevant observational data in addition to the sensor data described above. Additionally, the messaging module 364 enables the maintenance person 14 to send messages to the site supervisor 12 such as to convey the inability to complete a scheduled task 357 on time or the need to repair or refuel the maintenance equipment 114.”; Paragraph 116, “FIG. 5 is a schematic diagram of an example of the turf maintenance analytics engine 132 of FIG. 1. In certain embodiments, the turf maintenance analytics engine 132 shares components with the intelligent scheduler 130. The turf maintenance analytics engine 132 includes a turf site database 502 that stores data on the various areas and features within the turf site 10. In certain embodiments, the turf site database 502 is shared with the intelligent scheduler 130 such that the turf site databases 402, 502 are the same database utilized by both the turf maintenance analytics engine 132 and the intelligent scheduler 130 to perform their assigned functions. In certain embodiments, the turf site database 502 stores additional data such as the historical conditions of the various areas and features within the turf site 10.”; Paragraph 129, “In certain embodiments, the algorithms 512 can generate automated route mapping for improved efficiency. For example, an optimized route for mowing the turf site 10 can be determined by the algorithms 512 based on historical performance.”; Paragraph 103, “In further embodiments, the algorithms 512 can be used to identify problems (e.g., chemical sprayer went next to pond just before fish kill), or can be used for process validation to prove that steps were properly performed (e.g., chemical sprayer never went near the pond).”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management.")
Claim(s) 54 –
Wykman in view of Ries disclose the limitations claim
Wykman does not explicitly disclose the following, however, in analogous art of property management and maintenance, Ries discloses the following:
wherein, for each piece of the improvement information, the information transmitted to a terminal corresponding to an owner of the lawn is different from the information transmitted to a terminal corresponding to a contractor that provides a lawn maintenance service. (Ries: Paragraph 29, “In certain embodiments, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 are operated by a common entity such as an owner of the turf site 10 or the site supervisor 12. Alternatively, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 can be independently operated by different entities such as contractors or sub-contractors hired by the owner of the turf site 10 or the site supervisor 12.”; Paragraph 66, “Still referring to FIG. 2, the control interface 102 further includes a messaging module 314 that enables the user such as the site supervisor 12 to send messages to the maintenance personnel 14, and to receive messages from the maintenance personnel 14. Advantageously, the messaging module 314 can enhance the coordination between the site supervisor 12 and the maintenance personnel 14 during performance of a turf maintenance job. Illustrative examples of the messaging between the site supervisor 12 and maintenance personnel 14 include the site supervisor 12 messaging an assignment of a task to the maintenance personnel 14, an update to a previously assigned task, weather warnings, an instruction to call the site supervisor 12, and the like. Additionally, the messaging module 314 can automatically translate a message from the site supervisor into another language for improved communication between the site supervisor 12 and the maintenance personnel 14. For example, the messaging module 314 can automatically translate a message from the site supervisor 12 in English into Spanish, and then relay the message in Spanish to the maintenance personnel 14 for improved communication.”; Paragraph 101, “Additionally, in certain embodiments, the intelligent scheduler 130 can automatically detect problems with the maintenance equipment 114, and alert the maintenance person 14 assigned to operate the equipment to return to the garage. For example, intelligent scheduler 130 can monitor the operation and fuel usage of the maintenance equipment 114 (e.g., by using a sensor on the maintenance equipment 114 that detects fuel level) to alert the maintenance person 14 operating the equipment that the fuel is low, and that the equipment should return to the garage for refueling before, during or after the maintenance person 14 completes a scheduled task. The intelligent scheduler 130 can push equipment recall notices to the site supervisor 12, owner of the maintenance equipment 114, or owner of the turf site 10.”; Paragraph 103, “When the intelligent scheduler 130 receives a maintenance alert, the intelligent scheduler 130 automatically alerts a mechanic at the garage to prepare for the return of the maintenance equipment 114 for service, and can identify and communicate the maintenance issue to the mechanic before the maintenance equipment returns to the garage so that the mechanic can order spare parts as needed. Examples of servicing the maintenance equipment 114 can include software/firmware updates, electrical system repairs, and the like. In some instances, certain maintenance issues may require full component replacement from third-party vendors. The intelligent scheduler 130 can also adjust the scheduling of tasks when the maintenance equipment 114 needs to be repaired or taken out of service.”; Paragraph 132, “In certain embodiments, the turf maintenance analytics engine 132 includes an additional turf sites database 514 that stores data from other turf sites for comparison with the data from the turf site 10. The other turf sites can be managed by the same site supervisor or management company, or can be owned by the same owner. In certain embodiments, the data from the other turf sites is provided as anonymized averages to preserve the data privacy of the other turf sites.”; Paragraph 111, “In some embodiments, a message is received from the maintenance person 14 that includes the observed issue and the location of the maintenance person 14. The message can be sent from the display device 148 utilized by the maintenance person 14 such as a portable tablet computer or a smartphone, or a display device mounted to the maintenance equipment 114 used by the maintenance personnel 14. In some embodiments, the message is sent through a wireless cellular network. In some embodiments, the message is received by the display device utilized by the site supervisor 12 such that the site supervisor is notified about the observed issue.”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management.")
Claim(s) 55 –
Wykman in view of Ries disclose the limitations claim
Wykman does not explicitly disclose the following, however, in analogous art of property management and maintenance, Ries discloses the following:
wherein, for each piece of the improvement information, a transmission destination sorted between a terminal corresponding to an owner of the lawn and a terminal corresponding to a contractor that provides a lawn maintenance service is changeable. (Ries: Paragraph 29, “In certain embodiments, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 are operated by a common entity such as an owner of the turf site 10 or the site supervisor 12. Alternatively, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 can be independently operated by different entities such as contractors or sub-contractors hired by the owner of the turf site 10 or the site supervisor 12.”; Paragraph 66, “Still referring to FIG. 2, the control interface 102 further includes a messaging module 314 that enables the user such as the site supervisor 12 to send messages to the maintenance personnel 14, and to receive messages from the maintenance personnel 14. Advantageously, the messaging module 314 can enhance the coordination between the site supervisor 12 and the maintenance personnel 14 during performance of a turf maintenance job. Illustrative examples of the messaging between the site supervisor 12 and maintenance personnel 14 include the site supervisor 12 messaging an assignment of a task to the maintenance personnel 14, an update to a previously assigned task, weather warnings, an instruction to call the site supervisor 12, and the like. Additionally, the messaging module 314 can automatically translate a message from the site supervisor into another language for improved communication between the site supervisor 12 and the maintenance personnel 14. For example, the messaging module 314 can automatically translate a message from the site supervisor 12 in English into Spanish, and then relay the message in Spanish to the maintenance personnel 14 for improved communication.”; Paragraph 101, “Additionally, in certain embodiments, the intelligent scheduler 130 can automatically detect problems with the maintenance equipment 114, and alert the maintenance person 14 assigned to operate the equipment to return to the garage. For example, intelligent scheduler 130 can monitor the operation and fuel usage of the maintenance equipment 114 (e.g., by using a sensor on the maintenance equipment 114 that detects fuel level) to alert the maintenance person 14 operating the equipment that the fuel is low, and that the equipment should return to the garage for refueling before, during or after the maintenance person 14 completes a scheduled task. The intelligent scheduler 130 can push equipment recall notices to the site supervisor 12, owner of the maintenance equipment 114, or owner of the turf site 10.”; Paragraph 103, “When the intelligent scheduler 130 receives a maintenance alert, the intelligent scheduler 130 automatically alerts a mechanic at the garage to prepare for the return of the maintenance equipment 114 for service, and can identify and communicate the maintenance issue to the mechanic before the maintenance equipment returns to the garage so that the mechanic can order spare parts as needed. Examples of servicing the maintenance equipment 114 can include software/firmware updates, electrical system repairs, and the like. In some instances, certain maintenance issues may require full component replacement from third-party vendors. The intelligent scheduler 130 can also adjust the scheduling of tasks when the maintenance equipment 114 needs to be repaired or taken out of service.”; Paragraph 132, “In certain embodiments, the turf maintenance analytics engine 132 includes an additional turf sites database 514 that stores data from other turf sites for comparison with the data from the turf site 10. The other turf sites can be managed by the same site supervisor or management company, or can be owned by the same owner. In certain embodiments, the data from the other turf sites is provided as anonymized averages to preserve the data privacy of the other turf sites.”; Paragraph 111, “In some embodiments, a message is received from the maintenance person 14 that includes the observed issue and the location of the maintenance person 14. The message can be sent from the display device 148 utilized by the maintenance person 14 such as a portable tablet computer or a smartphone, or a display device mounted to the maintenance equipment 114 used by the maintenance personnel 14. In some embodiments, the message is sent through a wireless cellular network. In some embodiments, the message is received by the display device utilized by the site supervisor 12 such that the site supervisor is notified about the observed issue.”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management.")
Claim(s) 56 –
Wykman discloses the following limitations:
receiving positional information of a lawn mower detected by a position sensor installed at the lawn mower; (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
receiving condition information of a lawn detected by a condition sensor installed at the lawn mower; and (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
using a processor, analyzing the condition information per piece of the positional information and generating and outputting improvement information indicating a method for improvement of condition of the lawn per piece of the positional information, (Wykman: Paragraph 6, "In an example embodiment, a robotic vehicle for lawn monitoring is provided. The robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, and a vegetation analyzer module configured to analyze data received from the sensor network to determine lawn wellness information."; Paragraph 50, "In some embodiments, the robotic vehicle 15 may further act as a mobile sensor. In this regard, for example, the robotic vehicle 15 may carry a camera 95 on board, and the camera 95 may record video or obtain image data associated with respective locations or zones. The image data, in addition to its potential use in location determination described above, may be analyzed to determine the color, size, length, or overall health of vegetation or may be used to augment security functions. Information regarding color, size, length, or overall health of vegetation may then be used to determine the growing conditions impacting the vegetation."; Paragraph 88, "Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise communicate with, the positioning module 780 to, for example, determine vehicle speed/direction, vehicle location, vehicle orientation and/or the like. Sensors may also be used to determine motor run time, machine work time, and other operational parameters. In some embodiments, positioning and/or orientation sensors (e.g., global positioning system (GPS) receiver, SIM card, and/or accelerometer) may be included to monitor, display and/or record data regarding vehicle position and/or orientation as part of the positioning module 780."; Paragraph 89, "In an example embodiment, the vegetation analyzer 770 may be configured to utilize one or more sensors (e.g., of the sensor network 30) to determine plant stress and direct lawn maintenance in response to the plant stress. As such, the robotic mower 15 (or more specifically, the control circuitry 12) may enable continuous monitoring and maintenance of lawn wellness. The vegetation analyzer 770 may therefore be configured to detect water stress and nutrient stress in the lawn. In some cases, the vegetation analyzer 770 may be further configured to detect weed infestations or pest infestations. Various sensors of sensor network 30 of the robotic mower 15 may be included as a portion of, or otherwise, communicate with, the vegetation analyzer 770 to, for example, determine lawn conditions in various portions of the lawn."; Paragraph 25, "The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as "zones," and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.")
wherein the positional information and the condition information are detected while the lawn mower is mowing the lawn, (Wykman: Paragraph 53, “As such, for example, watering (or some other task) may be commenced and the system 10 may employ the sensor network 30 in combination with operation of the robotic vehicle 15 to monitor the distribution of the water (or fertilizer, etc.). The sensor network 30 may be transported to different locations, or data may be collected at different locations by the robotic vehicle 15 and then be used to provide feedback via the application manager 40 to direct more or less watering (or other resource utilization) in certain areas.”; Paragraph 65, “If a sensor network 30 is employed, the sensor network 30 may include sensors related to positional determination (e.g., a GPS receiver, an accelerometer, a camera, an inertial measurement unit and/or the like). Thus, for example, positional determinations may be made using GPS, inertial navigation, optical flow, visual location (e.g., VSLAM) and/or other positioning techniques or combinations thereof. Accordingly, the sensors may be used, at least in part, for determining the location of the robotic mower 15 relative to boundaries or other points of interest (e.g., a starting point or other key features) of the parcel 200, or determining a position history or track of the robotic mower 15 over time. The sensors may also detect collision, tipping over, or various fault conditions. In some cases, the sensors may also or alternatively collect data regarding various measurable parameters (e.g., moisture, nutrient stress, weed infestations, pest infestations, etc.) associated with particular locations on the parcel 200.”; Paragraph 101, “Inertial navigation systems may suffer from integration drift over time. Accordingly, inertial navigation systems may require a periodic position correction, which may be accomplished by getting a position fix from another more accurate method or by fixing a position of the robotic mower 15 relative to a known location. For example, navigation conducted via the IMU 850 may be used for robotic mower 15 operation for a period of time, and then a correction may be inserted when a GPS fix is obtained on robotic mower position. As an example alternative, the IMU 850 determined position may be updated every time the robotic mower 15 returns to the charge station 540 (which may be assumed to be at a fixed location). In still other examples, known reference points may be disposed at one or more locations on the parcel 200 and the robotic mower 15 may get a fix relative to any of such known reference points when the opportunity presents itself. The IMU 850 determined position may then be updated with the more accurate fix information. In some embodiments, the GPS receiver 852 may be embodied as a real time kinematic (RTK)—GPS receiver. As such, the GPS receiver 852 may employ satellite based positioning in conjunction with GPS, GLONASS, Galileo, GNSS, and/or the like to enhance accuracy of the GPS receiver 852. In some cases, carrier-phase enhancement may be employed such that, for example, in addition to the information content of signals received, the phase of the carrier wave may be examined to provide real-time corrections that can enhance accuracy.”)
Wykman does not explicitly disclose the following, however, in analogous art of property management and maintenance, Ries discloses the following:
wherein, according to a type of the improvement information, the system sorts information to be transmitted to a terminal corresponding to an owner of the lawn and to a terminal corresponding to a contractor that provides a lawn maintenance service . (Ries: Paragraph 29, “In certain embodiments, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 are operated by a common entity such as an owner of the turf site 10 or the site supervisor 12. Alternatively, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 can be independently operated by different entities such as contractors or sub-contractors hired by the owner of the turf site 10 or the site supervisor 12.”; Paragraph 66, “Still referring to FIG. 2, the control interface 102 further includes a messaging module 314 that enables the user such as the site supervisor 12 to send messages to the maintenance personnel 14, and to receive messages from the maintenance personnel 14. Advantageously, the messaging module 314 can enhance the coordination between the site supervisor 12 and the maintenance personnel 14 during performance of a turf maintenance job. Illustrative examples of the messaging between the site supervisor 12 and maintenance personnel 14 include the site supervisor 12 messaging an assignment of a task to the maintenance personnel 14, an update to a previously assigned task, weather warnings, an instruction to call the site supervisor 12, and the like. Additionally, the messaging module 314 can automatically translate a message from the site supervisor into another language for improved communication between the site supervisor 12 and the maintenance personnel 14. For example, the messaging module 314 can automatically translate a message from the site supervisor 12 in English into Spanish, and then relay the message in Spanish to the maintenance personnel 14 for improved communication.”; Paragraph 101, “Additionally, in certain embodiments, the intelligent scheduler 130 can automatically detect problems with the maintenance equipment 114, and alert the maintenance person 14 assigned to operate the equipment to return to the garage. For example, intelligent scheduler 130 can monitor the operation and fuel usage of the maintenance equipment 114 (e.g., by using a sensor on the maintenance equipment 114 that detects fuel level) to alert the maintenance person 14 operating the equipment that the fuel is low, and that the equipment should return to the garage for refueling before, during or after the maintenance person 14 completes a scheduled task. The intelligent scheduler 130 can push equipment recall notices to the site supervisor 12, owner of the maintenance equipment 114, or owner of the turf site 10.”; Paragraph 103, “When the intelligent scheduler 130 receives a maintenance alert, the intelligent scheduler 130 automatically alerts a mechanic at the garage to prepare for the return of the maintenance equipment 114 for service, and can identify and communicate the maintenance issue to the mechanic before the maintenance equipment returns to the garage so that the mechanic can order spare parts as needed. Examples of servicing the maintenance equipment 114 can include software/firmware updates, electrical system repairs, and the like. In some instances, certain maintenance issues may require full component replacement from third-party vendors. The intelligent scheduler 130 can also adjust the scheduling of tasks when the maintenance equipment 114 needs to be repaired or taken out of service.”; Paragraph 132, “In certain embodiments, the turf maintenance analytics engine 132 includes an additional turf sites database 514 that stores data from other turf sites for comparison with the data from the turf site 10. The other turf sites can be managed by the same site supervisor or management company, or can be owned by the same owner. In certain embodiments, the data from the other turf sites is provided as anonymized averages to preserve the data privacy of the other turf sites.”; Paragraph 111, “In some embodiments, a message is received from the maintenance person 14 that includes the observed issue and the location of the maintenance person 14. The message can be sent from the display device 148 utilized by the maintenance person 14 such as a portable tablet computer or a smartphone, or a display device mounted to the maintenance equipment 114 used by the maintenance personnel 14. In some embodiments, the message is sent through a wireless cellular network. In some embodiments, the message is received by the display device utilized by the site supervisor 12 such that the site supervisor is notified about the observed issue.”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management.")
Claim(s) 45 –
Wykman in view of Ries disclose the limitations of claims 22 and 56
Wykman further discloses the following:
wherein the improvement information includes the type of the improvement operation and a schedule for performing the improvement operation Wykman: Paragraph 25, “The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as “zones,” and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.”; Paragraph 32, “The user interface 130 (if implemented) may be in communication with the processing circuitry 110 to receive an indication of a user input at the user interface 130 and/or to provide an audible, visual, mechanical or other output to the user. As such, the user interface 130 may include, for example, a display, one or more buttons or keys (e.g., function buttons or a keyboard), and/or other input/output mechanisms (e.g., microphone, speakers, cursor, joystick, lights and/or the like). The user interface 130 may be configured to provide alerts, warnings and/or notifications to the user or operator responsive to various trigger conditions being detected (e.g., via the sensor network 30 or other components). In some cases, the user interface 130 may be configured to generate such alerts, warnings and/or notifications in response to plant growing conditions being out of specification or out of recommended ranges. System malfunctions, damage or tampering with equipment, equipment theft and other component related stimuli may also be defined as triggers for generation of the alerts, warnings and/or notifications. The alerts, warnings and/or notifications may be generated via light, sound, visual display, or other devices that may be connected to or part of the application manager 40. In some cases, the notifications may be provided by text message, email, or mobile application.”; Paragraph 60, “In some cases, the application manager 40 may take automated action to improve growing conditions by controlling watering, fertilizing, cutting, lighting or other activities based on a determination that current conditions are not optimal. However, in other situations, the application manager 40 may be configured to provide an alert or instructions locally or via a smart phone or other remote device, to instruct or otherwise inform the owner/operator that some changes to current conditions may be advisable. The specific actions recommended may be identified, or an alert to check certain conditions may be provided. Accordingly, a relatively robust system for control of lawn conditions may be provided in an automated fashion. The result may be deemed to operate as a “smart lawn” that provides efficient control to achieve optimal growing conditions.”; Paragraph 112, “FIG. 13 illustrates a control flow diagram of one example of how the robotic mower 10 can be operated in relation to using the sensors thereon in accordance with an example embodiment. As shown in FIG. 13, operation may begin with receiving position data from a positioning module in operation 951 and receiving sensor data from a sensor network including one or more sensors disposed on a parcel of land in operation 952. The operation may continue by determining current lawn conditions on the parcel based on the sensor data using a vegetation analyzer module in operation 953. The operation may further continue by deciding whether the lawn is healthy by comparing current lawn conditions to desirable lawn conditions associated with vegetation planted on the parcel of land in operation 954. If the lawn is healthy, then the operation continues by maintaining the current maintenance and monitoring schedule in operation 955a. However, if the lawn is not healthy, then the operation continues by remedying plant stress and/or any infestations with the appropriate means (e.g., watering, fertilizing, etc.) in operation 955b.”)
Claim(s) 46 –
Wykman in view of Ries disclose the limitations of claims 22 and 56
Wykman further discloses the following:
wherein the system suggests a maintenance time according to the owner's schedule or the service provider's schedule. (Wykman: Paragraph 25, “The system may therefore employ any combination of fixed and/or mobile sensors that gather data that relates to specific segments of the parcel that may correspond to each respective one of the various areas mentioned above. The specific segments may have different lawn conditions therein, and therefore may optimally have different growing conditions desirable in connection with each respective one of the segments. The owner/operator may define the specific segments, which may be referred to as “zones,” and identify the lawn conditions associated with each zone or the growing conditions desired for each zone. In some cases, the processing circuitry may be equipped to correlate desirable growing conditions to an identified plant species based on stored information associated with each plant species from a database or online resource. Accordingly, each zone will have corresponding growing condition and lawn wellness parameters associated therewith, and the growing condition and lawn wellness parameters may define the desired growing conditions (e.g., any or all of moisture level, temperature, lighting level, pH, and/or the like) for the corresponding zone. In some cases, the zones may further be associated with the corresponding task performance equipment that may be employed to alter the growing conditions in the respective zones and therefore act as potential resources for performing tasks. The resources may be associated with the zones in such a way as to define the specific resources (e.g., a resource list) that is available for use in any given zone. The processing circuitry may then either direct operation of assets from the resource list to achieve a desired outcome or may provide instructions or suggestions to the owner/operator regarding the assets from the resource list that could be employed to achieve a desired outcome. Alternatively, the processing circuitry may merely inform the owner/operator of the situation, and the owner/operator may be relied upon to take corrective actions as needed.”; Paragraph 32, “The user interface 130 (if implemented) may be in communication with the processing circuitry 110 to receive an indication of a user input at the user interface 130 and/or to provide an audible, visual, mechanical or other output to the user. As such, the user interface 130 may include, for example, a display, one or more buttons or keys (e.g., function buttons or a keyboard), and/or other input/output mechanisms (e.g., microphone, speakers, cursor, joystick, lights and/or the like). The user interface 130 may be configured to provide alerts, warnings and/or notifications to the user or operator responsive to various trigger conditions being detected (e.g., via the sensor network 30 or other components). In some cases, the user interface 130 may be configured to generate such alerts, warnings and/or notifications in response to plant growing conditions being out of specification or out of recommended ranges. System malfunctions, damage or tampering with equipment, equipment theft and other component related stimuli may also be defined as triggers for generation of the alerts, warnings and/or notifications. The alerts, warnings and/or notifications may be generated via light, sound, visual display, or other devices that may be connected to or part of the application manager 40. In some cases, the notifications may be provided by text message, email, or mobile application.”; Paragraph 60, “In some cases, the application manager 40 may take automated action to improve growing conditions by controlling watering, fertilizing, cutting, lighting or other activities based on a determination that current conditions are not optimal. However, in other situations, the application manager 40 may be configured to provide an alert or instructions locally or via a smart phone or other remote device, to instruct or otherwise inform the owner/operator that some changes to current conditions may be advisable. The specific actions recommended may be identified, or an alert to check certain conditions may be provided. Accordingly, a relatively robust system for control of lawn conditions may be provided in an automated fashion. The result may be deemed to operate as a “smart lawn” that provides efficient control to achieve optimal growing conditions.”; Paragraph 112, “FIG. 13 illustrates a control flow diagram of one example of how the robotic mower 10 can be operated in relation to using the sensors thereon in accordance with an example embodiment. As shown in FIG. 13, operation may begin with receiving position data from a positioning module in operation 951 and receiving sensor data from a sensor network including one or more sensors disposed on a parcel of land in operation 952. The operation may continue by determining current lawn conditions on the parcel based on the sensor data using a vegetation analyzer module in operation 953. The operation may further continue by deciding whether the lawn is healthy by comparing current lawn conditions to desirable lawn conditions associated with vegetation planted on the parcel of land in operation 954. If the lawn is healthy, then the operation continues by maintaining the current maintenance and monitoring schedule in operation 955a. However, if the lawn is not healthy, then the operation continues by remedying plant stress and/or any infestations with the appropriate means (e.g., watering, fertilizing, etc.) in operation 955b.”)
Claim(s) 27 and 53 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wykman (US 2018/0213731 Al) in view of Ries (US 2023/0214788 Al) and Anderson (US 2011/0153172 Al)
Claim(s) 27 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman does not explicitly disclose the following, however, in analogous art of property management and maintenance, Ries discloses the following:
…wherein the processor adjusts the control agent to be presented so that the control agent used as the improvement information in the past is not presented successively… (Ries: Paragraph 45, “The in-ground sensors 118 provide data relevant to the conditions of an area within the turf site 10. The in-ground sensors 118 can include temperature sensors, moisture sensors, salinity sensors, and the like. Low moisture or high salinity detected in an area of the turf site 10 can indicate that the area is in danger of deterioration. The turf maintenance system 100 can use this data to schedule and/or adjust one or more tasks to improve the condition of the area.”; Paragraph 52, “The control interface 102 includes a task display module 306 that enables a user such as the site supervisor 12 to add, remove, or adjust scheduled tasks 307a-307z for a turf maintenance job based on data from one or more of the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112. In some embodiments, the task display module 306 enables the site supervisor 12 to manually add, remove, or adjust the scheduled tasks 307, while in other embodiments, the task display module 306 can automatically add, remove, or adjust the scheduled tasks 307 based on the data from one or more of the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112. In some further embodiments, the task display module 306 provides a recommendation for adding, removing, or adjusting a scheduled task 307 that the site supervisor can accept or reject by using the control interface 102.”; Paragraph 63, “The site supervisor 12 can select the irrigation control module 310 to expand it, and thereby view more detailed information of the irrigation system 110. For example, the irrigation control module 310 when expanded can enable the site supervisor 12 to disable or adjust the schedule of a sprinkler 116 or a subset of the sprinklers 116 installed in the turf site 10. The irrigation control module 310 enables the site supervisor 12 to control a single sprinkler or a subset of the sprinklers to provide more granular control of the irrigation system 110 that can be adjusted based on the needs of a given area within the turf site 10.”)
Wykman in view of Ries does not specifically disclose the following, however, in analogous art of property management and maintenance, Anderson discloses the following:
wherein the processor outputs a type or an amount of a control agent according to the identified type of the weeds as the improvement information… and wherein the processor analyzes the condition information to identify a type of weeds growing on the lawn and outputs control information according to the identified type of the weeds as the improvement information. (Anderson: Paragraph 55, "Computer 106 may transmit operational parameters to area management vehicle 108. The operational parameters may be specifications or options used by area management vehicle 108 during operation of area management vehicle 108. For example, computer 106 may transmit a specified change in elevation, a number of weed types to reduce, and a number of boundary types to detect. Additionally, computer 106 may transmit software updates, such as firmware updates, to area management vehicle 108."; Paragraph 127, "Turning now to FIG. 7, an illustration of an area management vehicle reducing a number of weeds is depicted in accordance with an illustrative embodiment. Vehicle 702 is an example implementation of area management vehicle 202 in FIG. 2. Vehicle 702 is depicted as reducing number of weeds 706. Number of weeds 706 is an example implementation of number of weeds 502 in FIG. 5."; Paragraph 130, "In this example, the area management process detects number of weeds 706. The area management process selects the resource contained within vehicle 702 that reduces number of weeds 706. In this example, the area management process causes distribution system 712 to distribute weed remover onto number of weeds 706. Distribution may take place for a period of time, an amount of weed remover, or until the area management process detects that weed remover has covered number of weeds 706 using image information."; Paragraph 147, "If the process determines that the image does not contain a border at operation 1206, the process determines if an inconsistency is present in the image (operation 1210). The inconsistency may be an inconsistency such as inconsistency 238 in FIG. 2. If the process determines that an inconsistency is present in the image, the process distributes a resource that is known to eliminate or reduce the presence of the inconsistency (operation 1212). For example, if the inconsistency is the presence of weeds, the process may distribute a resource, such as weed killer, to eliminate or reduce the presence of the weeds. The process terminates thereafter. If the process determines that an inconsistency is not present in the image at operation 1210, the process terminates.")
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. Anderson discloses a method for managing an outdoor area. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management."). It would have been further obvious at the time of Applicant's filed invention for one of ordinary skill in the art to combine the methods of Wykman in view of Ries with the teachings of Anderson in order to reduce the inconsistencies of a lawns health as disclosed by Anderson (Anderson: Paragraph 6, "The computer program product also comprises program code, stored on the computer readable storage medium, for causing a distribution system to distribute a resource in a number of portions of the area in which an inconsistency in the number of inconsistencies is identified responsive to the number of inconsistencies being present in the area.")
Claim(s) 53 –
Wykman in view of Ries and Anderson disclose the limitations of claims 22 and 27
Wykman does not explicitly disclose the following, however, in analogous art of property management and maintenance, Ries discloses the following:
wherein, according to the type of the improvement information, the processor sorts information to be transmitted to a terminal corresponding to an owner of the lawn and to a terminal corresponding to a contractor that provides a lawn maintenance service. (Ries: Paragraph 29, “In certain embodiments, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 are operated by a common entity such as an owner of the turf site 10 or the site supervisor 12. Alternatively, the weather service system 104, task management system 106, asset tracking system 108, irrigation system 110, and turf devices 112 can be independently operated by different entities such as contractors or sub-contractors hired by the owner of the turf site 10 or the site supervisor 12.”; Paragraph 101, “Additionally, in certain embodiments, the intelligent scheduler 130 can automatically detect problems with the maintenance equipment 114, and alert the maintenance person 14 assigned to operate the equipment to return to the garage. For example, intelligent scheduler 130 can monitor the operation and fuel usage of the maintenance equipment 114 (e.g., by using a sensor on the maintenance equipment 114 that detects fuel level) to alert the maintenance person 14 operating the equipment that the fuel is low, and that the equipment should return to the garage for refueling before, during or after the maintenance person 14 completes a scheduled task. The intelligent scheduler 130 can push equipment recall notices to the site supervisor 12, owner of the maintenance equipment 114, or owner of the turf site 10.”; Paragraph 132, “In certain embodiments, the turf maintenance analytics engine 132 includes an additional turf sites database 514 that stores data from other turf sites for comparison with the data from the turf site 10. The other turf sites can be managed by the same site supervisor or management company, or can be owned by the same owner. In certain embodiments, the data from the other turf sites is provided as anonymized averages to preserve the data privacy of the other turf sites.”; Paragraph 111, “In some embodiments, a message is received from the maintenance person 14 that includes the observed issue and the location of the maintenance person 14. The message can be sent from the display device 148 utilized by the maintenance person 14 such as a portable tablet computer or a smartphone, or a display device mounted to the maintenance equipment 114 used by the maintenance personnel 14. In some embodiments, the message is sent through a wireless cellular network. In some embodiments, the message is received by the display device utilized by the site supervisor 12 such that the site supervisor is notified about the observed issue.”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. Anderson discloses a method for managing an outdoor area. At the time of Applicant's filed invention one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman with the teachings of Ries in order to improve the quality and efficiency of property management as disclosed by Ries (Ries: Paragraph 4, "Challenges in turf management include the need to acquire accurate and relevant information in order to inform better management decisions, and to thereby improve the quality and efficiency of turf management.")
Claims 51 and 42 are rejected under 35 U.S.C. 103 as being unpatentable over Wykman (US 2018/0213731 Al) in view of Ries (US 2023/0214788 Al) and Kuchar (US 2008/0275765 A1)
Claim(s) 51 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman in view of Ries do not explicitly disclose the following, however, in analogous art of property management and maintenance, Kuchar discloses the following:
wherein, when the improvement information presented in the past was not effective, the processor presents improvement information different from the ineffective improvement information as the subsequent improvement information. (Kuchar: Paragraph 87, “As well as multiple configurations, the Sniper module can be used in many applications, some of these applications are; Provide service for lawn care companies (LCC) to better keep track of quality control; Keep track of applications for companies such as ChemLawn etc.; Integrate into GIS systems, as well as other, mapping and review systems; Joint information between all of the various concerned groups: EPA, USDA, BLM, FS, F&G, Federal list, State list, County Extension Agents, private land owners, the Monsanto's of the world, scientists, field applicators, universities, weed management agencies, libraries, individuals, etc.; Joint information for Health and Human Services, environmental concerns, etc.--to provide joint cooperation between all affected groups; Data for the government and commercial scientists to analyze spray effectiveness of the various conditions in which the sprays were applied; Determination of effectiveness of previous and continuous treatments. For example, if treatments are conducted over a number of years--are improvements being realized? Prolonged (multi-year) effect analysis; Ability to audit (individuals and project) work; Regulatory validation to keep sub-contractors honest; Information for the workforce to enable them to demonstrate the work completed (accountability information).”; Paragraph 88, “Other embodiments include communication between "Sniper" units so that if someone sprayed a plant the next operator to come along would not be allowed to provide a secondary application. Additionally control spray activation and quantities such as: disabling spray applications near steams and not allowing excessive amounts of spray to be applied to individual plants.”; Paragraph 122, “The "Validator" is a proposed SOD device that enables the automated recording of information used to record, in an intelligent manner, the effectiveness of an area previously treated. It is also used as a tool to confirm that the validation was conducted. This product is a subset of a "sniper" and provides a similar function, but is usually used by an entirely different group of individuals with a different set of goals. This device is used to specifically identify/determine whether or not particular weeds had previously been treated. This allows managers to analyze the effectiveness of those providing a previous treatment. Performance evaluations/validation can also be accomplished using logged `Sniper` data.”; Paragraph 124, “It is highly desirable that the unit be small and light. The "Validator" could be used in conjunction with a "Sniper" to allow for the treatment of plants not previously treated (i.e. treatment applied if no previous treatment occurred). In other words allow the "Validator" to make some progress in the area of treating weeds for those instances where previous treatment was ineffective; either by being missed entirely or the previous treatment having been ineffective.”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. Kuchar discloses a method for a configurable GIS system. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman in view of Ries with the teachings of Kuchar in order to improve the tracking of activity and performance over various task periods as disclosed by Kuchar (Kuchar: Paragraph 2, “The invention relates to generally to an apparatus for the collection of task oriented data, and more particularly to the collection of vocational data as it relates to the monitoring of man-hours, consumable materials used, and tracking operational hours of equipment, and tracking spatial location of workers, equipment, and jobsites.”)
Claim(s) 52 –
Wykman in view of Ries disclose the limitations of claim 22
Wykman in view of Ries do not explicitly disclose the following, however, in analogous art of property management and maintenance, Kuchar discloses the following:
wherein, when the improvement information presented in the past was effective, the processor presents the effective improvement information as the subsequent improvement information. (Kuchar: Paragraph 87, “As well as multiple configurations, the Sniper module can be used in many applications, some of these applications are; Provide service for lawn care companies (LCC) to better keep track of quality control; Keep track of applications for companies such as ChemLawn etc.; Integrate into GIS systems, as well as other, mapping and review systems; Joint information between all of the various concerned groups: EPA, USDA, BLM, FS, F&G, Federal list, State list, County Extension Agents, private land owners, the Monsanto's of the world, scientists, field applicators, universities, weed management agencies, libraries, individuals, etc.; Joint information for Health and Human Services, environmental concerns, etc.--to provide joint cooperation between all affected groups; Data for the government and commercial scientists to analyze spray effectiveness of the various conditions in which the sprays were applied; Determination of effectiveness of previous and continuous treatments. For example, if treatments are conducted over a number of years--are improvements being realized? Prolonged (multi-year) effect analysis; Ability to audit (individuals and project) work; Regulatory validation to keep sub-contractors honest; Information for the workforce to enable them to demonstrate the work completed (accountability information).”; Paragraph 88, “Other embodiments include communication between "Sniper" units so that if someone sprayed a plant the next operator to come along would not be allowed to provide a secondary application. Additionally control spray activation and quantities such as: disabling spray applications near steams and not allowing excessive amounts of spray to be applied to individual plants.”; Paragraph 122, “The "Validator" is a proposed SOD device that enables the automated recording of information used to record, in an intelligent manner, the effectiveness of an area previously treated. It is also used as a tool to confirm that the validation was conducted. This product is a subset of a "sniper" and provides a similar function, but is usually used by an entirely different group of individuals with a different set of goals. This device is used to specifically identify/determine whether or not particular weeds had previously been treated. This allows managers to analyze the effectiveness of those providing a previous treatment. Performance evaluations/validation can also be accomplished using logged `Sniper` data.”; Paragraph 124, “It is highly desirable that the unit be small and light. The "Validator" could be used in conjunction with a "Sniper" to allow for the treatment of plants not previously treated (i.e. treatment applied if no previous treatment occurred). In other words allow the "Validator" to make some progress in the area of treating weeds for those instances where previous treatment was ineffective; either by being missed entirely or the previous treatment having been ineffective.”)
Wykman discloses a method for a lawn maintenance system. Ries discloses a large scale turf property management system. Kuchar discloses a method for a configurable GIS system. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Wykman in view of Ries with the teachings of Kuchar in order to improve the tracking of activity and performance over various task periods as disclosed by Kuchar (Kuchar: Paragraph 2, “The invention relates to generally to an apparatus for the collection of task oriented data, and more particularly to the collection of vocational data as it relates to the monitoring of man-hours, consumable materials used, and tracking operational hours of equipment, and tracking spatial location of workers, equipment, and jobsites.”)
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Philip N Warner/Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624
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