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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 7-13 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 7 recites the limitation "the flood reported flood data" in line 1. There is insufficient antecedent basis for this limitation in the claim. Dependent claims 8-13 are objected for the same rationale.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-8, 10 and 13 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Appel et al. (US 20170169532 A1).
In regards to claim 1, Appel teaches a weather distribution system adapted to collect, analyze and distribute user reported flood data, the system comprising a user interface adapted for a user to report flood data, receive a flood alert and view displayed analyzed reported flood data relevant to the user, and a central cloud network adapted to collect, analyze, and distribute the reported flood data to the user (Paragraphs 14-18, 41, 42)
In one aspect, data sources may include dynamic sources and/or historical data repositories, examples of which may include but are not limited to, social media such as blogs, microblogs and news, for example, from one or more social media servers; complex networks such as social, business, work, information networks; weather forecasts (e.g., flood) based on historical data, real time weather data, which may be collected by sensors; official media and reports and/or records such as official broadcasted news, records about security issues and occurrences such as accident claims and/or reports and known epidemics, and others; local geo-referred information, including for example, those from electronic sensors; user information; records about incidents in an area, for example, from incident management systems; and other local information.[P-14]
Evaluations based on up-to-date information may provide precise and helpful resources in making decisions relating to geographical locations where uncertainties such as weather conditions may vary. Such evaluations may be relied on in making specific choices involving locations and/or destinations [P-15]
FIG. 1 is a diagram illustrating an overview of a system that may estimate geographic location information in one embodiment of the present disclosure. Information may be received from sources such as social media via a social media or network server 102, weather forecast information from one or more weather servers 104, media or reports from one or more news servers 106, one or more location devices and geographic information system servers 108, and other security information associated with the location 110. A location estimation system or module 112, executing on one or more hardware processors may, for instance, receive real-time information from the different servers 102, 104, 106, 108 and 110, perform analysis to determine or estimate information about a location. The location in one embodiment may be the current location of the user 114, or a location that a user inputs, for instance, as a destination location. For instance, the system with the user's permission may monitor the user's location. In another aspect, the user 114 may input a location to query the system about a specific region.[P-16]
FIG. 2 is a diagram illustrating a method that may estimate geographic location information in one embodiment of the present disclosure. At 202, a user profile information and context 204 may be obtained. The user profile contains, for example, user preferences, user information, visited places, any kind of information that may describe a user and places that user usually goes, for example, as input or permitted by the user to have access of. This information may be obtained smart phones or the like, sensor devices, wearable devices, social media, internal database of entities, and others, for example, as authorized or permitted by the user or appropriate entity. At 206, information from data sources may be obtained. Examples of data sources may include safety information 208, weather data 210, flooding information 212, and other information 214. Such information may be received by communicating with a respective server that manages and stores the respective information.[P-17]
At 216, social media data 218, for example, from a social media server, may be received related to the geographic location and combined with the information received at 206. For instance, a machine learning algorithm executed on one or more hardware processors may combine information of social media reported by social media users with other data sources obtained in 206.[P-18]
FIG. 5 illustrates a schematic of an example computer or processing system that may implement a context-aware location estimation system in one embodiment of the present disclosure. The computer system is only one example of a suitable processing system and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the methodology described herein. The processing system shown may be operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with the processing system shown in FIG. 5 may include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like.[P-41]
The computer system may be described in the general context of computer system executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. The computer system may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices. [P-42]
Appel then teaches the central cloud network comprising a report handler, wherein the report handler collects the reported flood data, analyzes the reported flood data and distributes the analyzed reported flood data to a memory database and a geographic information system (“GIS”) database (Paragraphs 17, 32, 40, 42)
a method that may estimate geographic location information in one embodiment of the present disclosure. At 202, a user profile information and context 204 may be obtained. The user profile contains, for example, user preferences, user information, visited places, any kind of information that may describe a user and places that user usually goes, for example, as input or permitted by the user to have access of. This information may be obtained smart phones or the like, sensor devices, wearable devices, social media, internal database of entities, and others, for example, as authorized or permitted by the user or appropriate entity. At 206, information from data sources may be obtained. Examples of data sources may include safety information 208, weather data 210, flooding information 212, and other information 214. Such information may be received by communicating with a respective server that manages and stores the respective information [P-17]
the present disclosure in one embodiment. At 402, a user may be interested in traveling to Z location, and 404 requests dynamic assessment for the destination location. At 406, one or more hardware processors implementing a methodology of the present disclosure in one embodiment may obtain data from a plurality of sources 408, e.g., servers that may store and/or manage information associated with social media, weather information and other information about the locality. User profile information 410 is also obtained.[P-32]
The methodology of the present disclosure may also improve a geographical information system (GIS) or technology, a system designed to capture, store, manipulate, analyze, manage, and present types of spatial or geographical data, for instance, by adding a feature that allows the GIS system for determine or estimate dynamic information about a geographic location. [P-40]
The computer system may be described in the general context of computer system executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. The computer system may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices [P-42]
the memory database, wherein the memory database stores user information and locations; the GIS database, wherein the GIS database records the analyzed reported flood data (Paragraph 40)
The methodology of the present disclosure may also improve a geographical information system (GIS) or technology, a system designed to capture, store, manipulate, analyze, manage, and present types of spatial or geographical data, for instance, by adding a feature that allows the GIS system for determine or estimate dynamic information about a geographic location. [P-40]
Furthermore, Appel teaches a notification trigger system, wherein the notification trigger system sends the user the flood alert and displays the analyzed reported flood data based on a user location; wherein the system automatically updates the displayed reported flood data in real-time (Paragraphs 22, 37)
the method may analyze the machine learning output and provide a ranking and recommendation to the user. For instance, the machine learning algorithm may classify geographical locations according to different levels of riskiness based on the captured data. For instance, the output may include a ranked list of places to avoid or to visit, parking lots to avoid or stop, walking path and time to use this path or avoid. For instance, feedback or an alert may be provided for the user about the geographic location, for example, a possible risk of that region associated with a specific subject such as flooding or safety. For example, consider the user context information such as the type of a vehicle the user is currently driving or using, an assessment may be provided as to the chances or probability that the user might have regarding a flooding problem or a safety problem, if the user were to be at the region at a defined time or current time. Context information may also include the activity of the user (e.g., returning from work, walking) at the time while in the specific region, which may be considered for providing the risk information associated with the region to the particular user. For instance, the methodology may allow a user to check whether the region is safe for parking or walking. In another aspect, entities such as an automobile insurance company or travel related company may utilize the methodology to send a warning message (for example SMS warning) or another alert in real-time about the geographic region to the user. In this way, the user may be warned of possible risks at the geographic location such as natural disaster, epidemics, weather related risks, or others [P-22]
Based on real-time risk determination, further actions may be taken, for example, reinforcing security in the regions. In one aspect, users who follow warning alerts (as determined from user decision and feedback information) may be made eligible for bonus, for example, by an insurance company. In another aspect, the alerts may signal an automobile and cause the automobile to steer away or drive in a different direction. For instance, an alert may be sent automatically to a control system that may control an automobile to automatically take a route to one or more of the recommended locations. In another aspect, an alert may be sent automatically to a navigation system or device associated with the automobile. Responsive to receiving the alert, the navigation system may automatically output, e.g., via automated voice or display, a different route to one or more of the recommended location instead.[P-37]
In regards to claim 2, Appel teaches the analyzed reported data provides flood information for specific local areas and streets (Paragraph 36)
In one embodiment, a real time user context (e.g., personalized) risk assessment method and system may estimate risk and make recommendations to a user based on multiple data sources, user profile and context. In one aspect, a user may check whether the geographic area or region or location is safe, for example, in various aspects, for example, for traveling, for example, for walking or parking. In one aspect, the system and methodology of the present disclosure in one embodiment may be invoked or utilized by an insurance company (e.g., travel, automobile, others) or another entity, for example, to send warning signals to customers, if for example, it is determined that risks exists or are predicted in the geographical locations. For instance, a short messaging system (SMS) warning may be sent about the area that is determined to have one or more risks, and direct the user to a different location that is determined to be safe. The geographic locations may include city, an area of a city, a specific parking area, specific road or street, and other regions, areas or locations. Risks may include safety concerns, e.g., due to weather such as flood risks, natural disaster, epidemic risks, and/or others. [P-36]
In regards to claim 3, Appel teaches the user reported flood data may be descriptive text, drop down menu selections and/or photo or video evidence (Paragraphs 22,36).
the method may analyze the machine learning output and provide a ranking and recommendation to the user. For instance, the machine learning algorithm may classify geographical locations according to different levels of riskiness based on the captured data. For instance, the output may include a ranked list of places to avoid or to visit, parking lots to avoid or stop, walking path and time to use this path or avoid. For instance, feedback or an alert may be provided for the user about the geographic location, for example, a possible risk of that region associated with a specific subject such as flooding or safety. For example, consider the user context information such as the type of a vehicle the user is currently driving or using, an assessment may be provided as to the chances or probability that the user might have regarding a flooding problem or a safety problem, if the user were to be at the region at a defined time or current time. Context information may also include the activity of the user (e.g., returning from work, walking) at the time while in the specific region, which may be considered for providing the risk information associated with the region to the particular user. For instance, the methodology may allow a user to check whether the region is safe for parking or walking. In another aspect, entities such as an automobile insurance company or travel related company may utilize the methodology to send a warning message (for example SMS warning) or another alert in real-time about the geographic region to the user. In this way, the user may be warned of possible risks at the geographic location such as natural disaster, epidemics, weather related risks, or others.[P-22]
In one embodiment, a real time user context (e.g., personalized) risk assessment method and system may estimate risk and make recommendations to a user based on multiple data sources, user profile and context. In one aspect, a user may check whether the geographic area or region or location is safe, for example, in various aspects, for example, for traveling, for example, for walking or parking. In one aspect, the system and methodology of the present disclosure in one embodiment may be invoked or utilized by an insurance company (e.g., travel, automobile, others) or another entity, for example, to send warning signals to customers, if for example, it is determined that risks exists or are predicted in the geographical locations. For instance, a short messaging system (SMS) warning may be sent about the area that is determined to have one or more risks, and direct the user to a different location that is determined to be safe. The geographic locations may include city, an area of a city, a specific parking area, specific road or street, and other regions, areas or locations. Risks may include safety concerns, e.g., due to weather such as flood risks, natural disaster, epidemic risks, and/or others. [P-36]
In regards to claim 4, Appel teaches the GIS database and the memory database record a location of the analyzed reported data, a location of the user, and a timestamp (Paragraphs 16, 27)
FIG. 1 is a diagram illustrating an overview of a system that may estimate geographic location information in one embodiment of the present disclosure. Information may be received from sources such as social media via a social media or network server 102, weather forecast information from one or more weather servers 104, media or reports from one or more news servers 106, one or more location devices and geographic information system servers 108, and other security information associated with the location 110. A location estimation system or module 112, executing on one or more hardware processors may, for instance, receive real-time information from the different servers 102, 104, 106, 108 and 110, perform analysis to determine or estimate information about a location. The location in one embodiment may be the current location of the user 114, or a location that a user inputs, for instance, as a destination location. For instance, the system with the user's permission may monitor the user's location. In another aspect, the user 114 may input a location to query the system about a specific region.[P-16]
At 320, real time monitoring function running on one or more processors may receive the user profile and context information 318 and the combined information about the geographical region 316 captured from multiple diverse sources. Real time information, for example, may be monitored using social media, a global positioning system (GPS) device or functionality in a user device (e.g., a smart phone or the like) and news information. Real time monitoring at 320 may be performed by a computer server, a sensor from an internet of things (IOT) network, and/or a device built specifically for monitoring a geographic location.[P-27]
In regards to claim 5, Appel teaches the GIS database conducts advanced analysis of the analyzed reported flood data and queries of the analyzed reported flood data (Paragraph 16),
FIG. 1 is a diagram illustrating an overview of a system that may estimate geographic location information in one embodiment of the present disclosure. Information may be received from sources such as social media via a social media or network server 102, weather forecast information from one or more weather servers 104, media or reports from one or more news servers 106, one or more location devices and geographic information system servers 108, and other security information associated with the location 110. A location estimation system or module 112, executing on one or more hardware processors may, for instance, receive real-time information from the different servers 102, 104, 106, 108 and 110, perform analysis to determine or estimate information about a location. The location in one embodiment may be the current location of the user 114, or a location that a user inputs, for instance, as a destination location. For instance, the system with the user's permission may monitor the user's location. In another aspect, the user 114 may input a location to query the system about a specific region[P-16]
In regards to claim 6, Appel teaches the queries are run using recorded historical analyzed flood data (Paragraphs 14, 16, 19)
In one aspect, data sources may include dynamic sources and/or historical data repositories, examples of which may include but are not limited to, social media such as blogs, microblogs and news, for example, from one or more social media servers; complex networks such as social, business, work, information networks; weather forecasts (e.g., flood) based on historical data, real time weather data, which may be collected by sensors; official media and reports and/or records such as official broadcasted news, records about security issues and occurrences such as accident claims and/or reports and known epidemics, and others; local geo-referred information, including for example, those from electronic sensors; user information; records about incidents in an area, for example, from incident management systems; and other local information.[P-14]
FIG. 1 is a diagram illustrating an overview of a system that may estimate geographic location information in one embodiment of the present disclosure. Information may be received from sources such as social media via a social media or network server 102, weather forecast information from one or more weather servers 104, media or reports from one or more news servers 106, one or more location devices and geographic information system servers 108, and other security information associated with the location 110. A location estimation system or module 112, executing on one or more hardware processors may, for instance, receive real-time information from the different servers 102, 104, 106, 108 and 110, perform analysis to determine or estimate information about a location. The location in one embodiment may be the current location of the user 114, or a location that a user inputs, for instance, as a destination location. For instance, the system with the user's permission may monitor the user's location. In another aspect, the user 114 may input a location to query the system about a specific region [P-16]
The system monitors the user steps or the user can query the system about a specific region, the system analyses several data sources using real-time information such as user profile and context, social media and network, weather system and other security database and official media and reports.[P-19]
In regards to claim 7, Appel teaches a method for collecting and distributing the flood reported flood data in real time to a user, the method comprising; one or more users registering on a flood data system (Paragraphs 16, 22, 36)
FIG. 1 is a diagram illustrating an overview of a system that may estimate geographic location information in one embodiment of the present disclosure. Information may be received from sources such as social media via a social media or network server 102, weather forecast information from one or more weather servers 104, media or reports from one or more news servers 106, one or more location devices and geographic information system servers 108, and other security information associated with the location 110. A location estimation system or module 112, executing on one or more hardware processors may, for instance, receive real-time information from the different servers 102, 104, 106, 108 and 110, perform analysis to determine or estimate information about a location. The location in one embodiment may be the current location of the user 114, or a location that a user inputs, for instance, as a destination location. For instance, the system with the user's permission may monitor the user's location. In another aspect, the user 114 may input a location to query the system about a specific region.[P-16]
the method may analyze the machine learning output and provide a ranking and recommendation to the user. For instance, the machine learning algorithm may classify geographical locations according to different levels of riskiness based on the captured data. For instance, the output may include a ranked list of places to avoid or to visit, parking lots to avoid or stop, walking path and time to use this path or avoid. For instance, feedback or an alert may be provided for the user about the geographic location, for example, a possible risk of that region associated with a specific subject such as flooding or safety. For example, consider the user context information such as the type of a vehicle the user is currently driving or using, an assessment may be provided as to the chances or probability that the user might have regarding a flooding problem or a safety problem, if the user were to be at the region at a defined time or current time. Context information may also include the activity of the user (e.g., returning from work, walking) at the time while in the specific region, which may be considered for providing the risk information associated with the region to the particular user. For instance, the methodology may allow a user to check whether the region is safe for parking or walking. In another aspect, entities such as an automobile insurance company or travel related company may utilize the methodology to send a warning message (for example SMS warning) or another alert in real-time about the geographic region to the user. In this way, the user may be warned of possible risks at the geographic location such as natural disaster, epidemics, weather related risks, or others.[P-22]
In one embodiment, a real time user context (e.g., personalized) risk assessment method and system may estimate risk and make recommendations to a user based on multiple data sources, user profile and context. In one aspect, a user may check whether the geographic area or region or location is safe, for example, in various aspects, for example, for traveling, for example, for walking or parking. In one aspect, the system and methodology of the present disclosure in one embodiment may be invoked or utilized by an insurance company (e.g., travel, automobile, others) or another entity, for example, to send warning signals to customers, if for example, it is determined that risks exists or are predicted in the geographical locations. For instance, a short messaging system (SMS) warning may be sent about the area that is determined to have one or more risks, and direct the user to a different location that is determined to be safe. The geographic locations may include city, an area of a city, a specific parking area, specific road or street, and other regions, areas or locations. Risks may include safety concerns, e.g., due to weather such as flood risks, natural disaster, epidemic risks, and/or others.[P-36]
the one or more users logging into the flood data system; the one or more users reporting flood data to the system; analyzing the reported flood data; storing the analyzed reported flood data; and displaying all of the analyzed reported flood data on a user interface in a based on a user’s location (Paragraphs 22, 37, 40).
the method may analyze the machine learning output and provide a ranking and recommendation to the user. For instance, the machine learning algorithm may classify geographical locations according to different levels of riskiness based on the captured data. For instance, the output may include a ranked list of places to avoid or to visit, parking lots to avoid or stop, walking path and time to use this path or avoid. For instance, feedback or an alert may be provided for the user about the geographic location, for example, a possible risk of that region associated with a specific subject such as flooding or safety. For example, consider the user context information such as the type of a vehicle the user is currently driving or using, an assessment may be provided as to the chances or probability that the user might have regarding a flooding problem or a safety problem, if the user were to be at the region at a defined time or current time. Context information may also include the activity of the user (e.g., returning from work, walking) at the time while in the specific region, which may be considered for providing the risk information associated with the region to the particular user. For instance, the methodology may allow a user to check whether the region is safe for parking or walking. In another aspect, entities such as an automobile insurance company or travel related company may utilize the methodology to send a warning message (for example SMS warning) or another alert in real-time about the geographic region to the user. In this way, the user may be warned of possible risks at the geographic location such as natural disaster, epidemics, weather related risks, or others [P-22]
Based on real-time risk determination, further actions may be taken, for example, reinforcing security in the regions. In one aspect, users who follow warning alerts (as determined from user decision and feedback information) may be made eligible for bonus, for example, by an insurance company. In another aspect, the alerts may signal an automobile and cause the automobile to steer away or drive in a different direction. For instance, an alert may be sent automatically to a control system that may control an automobile to automatically take a route to one or more of the recommended locations. In another aspect, an alert may be sent automatically to a navigation system or device associated with the automobile. Responsive to receiving the alert, the navigation system may automatically output, e.g., via automated voice or display, a different route to one or more of the recommended location instead.[P-37]
The methodology of the present disclosure may also improve a geographical information system (GIS) or technology, a system designed to capture, store, manipulate, analyze, manage, and present types of spatial or geographical data, for instance, by adding a feature that allows the GIS system for determine or estimate dynamic information about a geographic location. [P-40]
In regards to claim 8, Appel teaches the displayed analyzed reported flood data includes specific street flood information, increasing or decreasing flood levels, road hazards and /or flood depth levels( Paragraphs 36)
In one embodiment, a real time user context (e.g., personalized) risk assessment method and system may estimate risk and make recommendations to a user based on multiple data sources, user profile and context. In one aspect, a user may check whether the geographic area or region or location is safe, for example, in various aspects, for example, for traveling, for example, for walking or parking. In one aspect, the system and methodology of the present disclosure in one embodiment may be invoked or utilized by an insurance company (e.g., travel, automobile, others) or another entity, for example, to send warning signals to customers, if for example, it is determined that risks exists or are predicted in the geographical locations. For instance, a short messaging system (SMS) warning may be sent about the area that is determined to have one or more risks, and direct the user to a different location that is determined to be safe. The geographic locations may include city, an area of a city, a specific parking area, specific road or street, and other regions, areas or locations. Risks may include safety concerns, e.g., due to weather such as flood risks, natural disaster, epidemic risks, and/or others. [P-36]
In regards to claim 10, Appel teaches providing an accurate evacuation route to the user based on the analyzed reported flood data to avoid a flooded travel route (Paragraph 37)
Based on real-time risk determination, further actions may be taken, for example, reinforcing security in the regions. In one aspect, users who follow warning alerts (as determined from user decision and feedback information) may be made eligible for bonus, for example, by an insurance company. In another aspect, the alerts may signal an automobile and cause the automobile to steer away or drive in a different direction. For instance, an alert may be sent automatically to a control system that may control an automobile to automatically take a route to one or more of the recommended locations. In another aspect, an alert may be sent automatically to a navigation system or device associated with the automobile. Responsive to receiving the alert, the navigation system may automatically output, e.g., via automated voice or display, a different route to one or more of the recommended location instead. [P-37]
In regards to claim 13, Appel teaches conducting an advanced search based off of historical analyzed reported flood data(Paragraphs 14, 16, 19)
In one aspect, data sources may include dynamic sources and/or historical data repositories, examples of which may include but are not limited to, social media such as blogs, microblogs and news, for example, from one or more social media servers; complex networks such as social, business, work, information networks; weather forecasts (e.g., flood) based on historical data, real time weather data, which may be collected by sensors; official media and reports and/or records such as official broadcasted news, records about security issues and occurrences such as accident claims and/or reports and known epidemics, and others; local geo-referred information, including for example, those from electronic sensors; user information; records about incidents in an area, for example, from incident management systems; and other local information.[P-14]
FIG. 1 is a diagram illustrating an overview of a system that may estimate geographic location information in one embodiment of the present disclosure. Information may be received from sources such as social media via a social media or network server 102, weather forecast information from one or more weather servers 104, media or reports from one or more news servers 106, one or more location devices and geographic information system servers 108, and other security information associated with the location 110. A location estimation system or module 112, executing on one or more hardware processors may, for instance, receive real-time information from the different servers 102, 104, 106, 108 and 110, perform analysis to determine or estimate information about a location. The location in one embodiment may be the current location of the user 114, or a location that a user inputs, for instance, as a destination location. For instance, the system with the user's permission may monitor the user's location. In another aspect, the user 114 may input a location to query the system about a specific region [P-16]
The system monitors the user steps or the user can query the system about a specific region, the system analyses several data sources using real-time information such as user profile and context, social media and network, weather system and other security database and official media and reports.[P-19]
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.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Appel et al. (US 20170169532 A1) in view of Wani et al. (US 20190318440 A1)
In regards to claim 11, Appel fails to teach the user updating a previously submitted flood report for an existing data point.
Wani on the other hand teaches the user updating a previously submitted flood report for an existing data point (Paragraph 47)
In another embodiment, a system includes a memory comprising instructions and one or more computer processors. The instructions, when executed by the one or more computer processors, cause the one or more computer processors to perform operations comprising: generating a prediction of water depth in a geographical region based on weather data for the geographical region and topography data for the geographical region; causing presentation of a flood inundation map showing the prediction of water depth in a user interface of a display device, the user interface comprising an option for entering flood mitigation measures; receiving the flood mitigation measures via the user interface; updating the topography data to include the received flood mitigation measures; generating an updated prediction of the water depth in the geographical region based on the updated topography data; and causing presentation of an updated flood inundation map in the user interface, the updated flood inundation map showing the updated prediction of the water depth and a geographical location of the flood mitigation measures.[P-47]
It would have been obvious to one of ordinary skill in the art during the filing date of the invention to combine Wani’s teaching with Appel’s teaching in order to improve real-time reports of hazardous weather location such that they can be distributed accordingly.
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Appel et al. (US 20170169532 A1) in view of Liutikas et al. (WO 2015021057 A1)
In regards to claim 12, Appel fails to teach filtering the displayed flood data information based on selected user criteria.
Liutikas on the other hand teaches filtering the displayed flood data information based on selected user criteria (Paragraph 53)
As mentioned above with reference to FIGS. 2-3, user selection of a search term prediction within suggestion interface 406 can query a search engine with the selected term, while user selection of a URL suggestion can direct the application (e.g., web browser) to the web page corresponding to the selected URL. It should be noted that the user can also select the one or more entries of contextual data presented within suggestion interface 406. In example aspects, in response to this selection, the application can be directed to a predetermined web page. For example, in response to user selection of the "flood warning" entry in suggestion interface 406, the application can be directed to a news article web page providing details for the flood. This web page can be selected, for example, based on popularity of the website and/or search activities by the user or other users. Alternatively, in response to the user selection, the application may query a search engine (e.g., hosted on server 1 10) with the text (or part of the text) corresponding to the selected entry. For example, a location-based query search can be requested for the search term "flood warning" with the location of "Los Angeles, CA." [P-53]
It would have been obvious to one of ordinary skill in the art during the filing date of the invention to combine Liutika’s teaching with Appel’s teaching in order to effectively aid the user in finding specific areas along their path affected by specific potential weather hazards
Allowable Subject Matter
Claim 9 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim 9 recites “The method as recited in claim 7, wherein reporting flood data comprises dropping a location pin where a flood exists, selecting the pin to see street level information, selecting a water icon once the pin is finalized, entering flood data and submitting a flood data report.“ During the time of the filing date of the said inventive entity, there was no prior art that taught the scope of the invention alongside its limitations of its parent claim.
Conclusion
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/ANTHONY D AFRIFA-KYEI/Examiner, Art Unit 2686
/BRIAN A ZIMMERMAN/Supervisory Patent Examiner, Art Unit 2686