DETAILED ACTION
Status of Claims
The following is a non-final, first office action in response to the communication filed 12/22/2022.
Claims 1-20 are currently pending and have been examined.
Information Disclosure Statement
Information Disclosure Statement received 5/21/2025 has been reviewed and considered.
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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 of the Subject Matter Eligibility Test entails considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter.
Claims 1-20 are directed to a method (process) and a system (machine or manufacture), respectively. As such, the claims are directed to statutory categories of invention.
If the claim recites a statutory category of invention, the claim requires further analysis in Step 2A. Step 2A of the Subject Matter Eligibility Test is a two-prong inquiry. In Prong One, examiners evaluate whether the claim recites a judicial exception.
Claim 1 recite abstract limitations, including those shown in bold below:
1. An adaptive layout generation system, comprising: a processor; a memory connected to the processor and configured to store an adaptive layout generation application; wherein the adaptive layout generation application generates design specifications for a workspace by directing the processor to: receive workspace data for a first time period relating to the workspace, wherein the workspace data comprises: sensor data from a set of one or more sensors in the workspace; and activity data related to work being performed in the workspace; analyze the received workspace data to determine workspace characteristics data, wherein the workspace characteristics data comprises: physical space data related to physical features in the workspace; work mode data related to types of work performed by users in the workspace; and user data related to individual users working in the workspace; generate layout data based on the workspace characteristic data, wherein the layout data comprises positions for a plurality of work zones in the workspace and a target work mode for each work zone of the plurality of work zones; generate a visual output that provides the design specifications including positions for the plurality of work zones and the target work mode for each work zone in the workspace based on the generated layout data; receive new workspace data for a new time period after the first time period; and generate at least one update for the generated visual output based on the new workspace data.
These limitations, as drafted, are a process that, under its broadest reasonable interpretation, cover performance of the limitations in the mind, or by a human using pen and paper, and therefore recite mental processes. More specifically, other than reciting a processing system, nothing in the claim element precludes the aforementioned steps from practically being performed in the human mind, or by a human using pen and paper. The mere recitation of a generic computer does not take the claim out of the mental process grouping. Thus, the claim recites an abstract idea.
Claims 10 and 11 recite analogous limitations to those presented above with respect to claim 1, and thereby recite an abstract idea for the same reason as those presented with respect to claim 1 above.
If the claim recites a judicial exception in step 2A Prong One , the claim requires further analysis in step 2A Prong Two. In step 2A Prong Two, examiners evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
Claim 1 recites additional elements, which are underlined below:
1. An adaptive layout generation system, comprising: a processor; a memory connected to the processor and configured to store an adaptive layout generation application; wherein the adaptive layout generation application generates design specifications for a workspace by directing the processor to: receive workspace data for a first time period relating to the workspace, wherein the workspace data comprises: sensor data from a set of one or more sensors in the workspace; and activity data related to work being performed in the workspace; analyze the received workspace data to determine workspace characteristics data, wherein the workspace characteristics data comprises: physical space data related to physical features in the workspace; work mode data related to types of work performed by users in the workspace; and user data related to individual users working in the workspace; generate layout data based on the workspace characteristic data, wherein the layout data comprises positions for a plurality of work zones in the workspace and a target work mode for each work zone of the plurality of work zones; generate a visual output that provides the design specifications including positions for the plurality of work zones and the target work mode for each work zone in the workspace based on the generated layout data; receive new workspace data for a new time period after the first time period; and generate at least one update for the generated visual output based on the new workspace data.
Regarding the data processing functions of the adaptive layout generation system, comprising: a processor; a memory connected to the processor and configured to store an adaptive layout generation application, the functions applied thereby are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Regarding the function of receiv[ing] workspace data for a first time period relating to the workspace, wherein the workspace data comprises: sensor data from a set of one or more sensors in the workspace; and activity data related to work being performed in the workspace”, the receiving step(s) from the sensors and from the external source is recited at a high level of generality (i.e. as a general means of gathering data for use in analyzing step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
Though note explicitly recited, if the visual layout was tied to a physical structure (i.e. a display), it would amount to mere post solution displaying, which is a form of insignificant extra-solution activity.
Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
If the additional elements do not integrate the exception into a practical application in step 2A Prong Two, then the claim is directed to the recited judicial exception, and requires further analysis under Step 2B to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
As discussed above, the adaptive layout generation system and its associated components amount to mere instructions to apply the exception. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). As discussed above, the receiving step amounts to extra-solution activity. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
As discussed above, if the visual layout was tied to a physical structure (i.e. a display), it would amount to extra-solution activity. MPEP 2106.05(d)(II), and the cases cited therein, including in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying of data is a well understood, routine, and conventional function.
In addition, with respect to all additional elements, the specification demonstrates the well-understood, routine, conventional nature of additional elements as it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. §112(a).
Dependent claims 2 and 12 further recite that use of a neural network that is trained using a dataset that includes layout data, which at this level of breadth, amounts no more than mere instructions to apply the exception using a generic computer component.
Dependent claims 3-4, 6-7, 9, 13-14, 16-17 and 19 merely act to further characterize previously identified abstract concepts. For the reasons described above with respect to claim 1, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea.
Dependent claims 5 and 15 act to further characterize the types of sensors comprised by the set of sensors, which amounts to merely indicating a field of use or technological environment in which to apply a judicial exception and cannot integrate the judicial exception into a practical application or amount to significantly more than the abstract idea itself.
Dependent claims 8 and 18 further recite the output of a control signal to modify an environment of the space. The output of a signal amounts to extra-solution activity. The Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here). While not positively recited, the actual control of environment modification, when recited at this level of breadth, merely amounts to apply it. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015).
Claim Rejections - 35 USC § 102
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.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 3-5, 7, 9-11, 13-15, 17 and 19 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Decamp et al. (US 20200219036).
Regarding claim 1, Decamp discloses:
1. An adaptive layout generation system, comprising: a processor; a memory connected to the processor and configured to store an adaptive layout generation application; wherein the adaptive layout generation application generates design specifications for a workspace by directing the processor to:
Decamp [0022]-[0023] FIG. 1 is a block diagram of a system 100 to manage a workspace 102, according to some embodiments.
Decamp [0041] The ability to monitor and/or predict use of the workstations 104 may enable more efficient use of office space, equipment, and power. For example, if it is determined that fewer workstations 104 are needed to accommodate the demand for workstations 104, savings may be made by reducing real estate, equipment, and/or electrical power costs. Also, the ability to monitor and/or predict use of the workstations 104 may enable planning ahead for increased demand for workstations 104 rather than be left with insufficient workstations 104 once it is realized that more workstations 104 are needed while additional real estate and/or equipment is/are acquired.
Decamp [0059] generally disclosing system applications and respective interfaces
receive workspace data for a first time period relating to the workspace (e.g., periods of time, such as day, month and season), wherein the workspace data comprises: sensor data from a set of one or more sensors in the workspace (e.g., power utilization, RFID, Iot sensor packs, etc.); and activity data related to work being performed in the workspace (e.g., schedule/assignments, authentication, power range, connection information, etc.);
Decamp [0023] The system network interface 116 of the system computer 138 and the network interface 112 of each docking station 106 enables the system computer 138 to manage the workspace 102 in a variety of ways. For example, the system computer 138 may be capable of: [0024] managing and monitoring consumption of power at the workstations 104 (e.g., capturing and analyzing individual device power consumption at the workstations 104, understand and optimize power consumption at the workstations 104, schedule power on/off events, etc.) [0025] managing workspace occupancy and scheduling (e.g., provide workspace utilization data, schedule Hotdesking environments where users are not permanently assigned to particular workstations 104, understand how a flexible workspace is working, maximize available space, reduce real estate costs, etc.). [0026] managing access and/or security of workstations through authentication tools such as radio frequency identification (RFID) (e.g., near field communication, or “NFC”). [0027] managing assets (e.g., automatic identification and inventorying of peripheral devices connected to docking stations 106, etc.) [0028] managing and actuating devices remotely (e.g., enable IT professionals to remotely manage the workspace 102, perform soft resets, power cycle, and firmware updates remotely, etc.) [0029] securing workspace and finding employees (e.g., identify and locate employees based on their scheduled workstations 104, provide enhanced network security, understand which of the workstations 104 employees are located in, enable employees to find each other, and enable employees to work more efficiently and securely, etc.
Decamp [0036] The docking station 106 at each of the workstations 104 of the workspace 102 may include a sensor 128 to monitor user occupancy at the corresponding one of the workstations 104 and generate sensor data relating to the user occupancy. By way of non-limiting example, the sensor 128 may include an infrared sensor and/or thermal sensor to confirm user occupancy. A thermal sensor may be configured to monitor ambient temperature at the corresponding one of the workstations 104 and generate sensor data relating to the ambient temperature. Other examples of the sensor 128 may include a temperature sensor, a humidity sensor, a power use sensor (e.g., to sense when power is being drawn from the docking station 106 and/or other power supplies at the workstations 104), an image sensor (e.g., a camera), a motion sensor, a capacitive sensor, a mechanical sensor (e.g., in a chair), a radio frequency identification (RFID) sensor (e.g., to detect an RFID signature produced by a device such as an NFC device carried by the user and/or the computer device 132), a battery charge sensor of a battery that powers the sensor 128 or the IoT sensor pack 210 of FIG. 2, other sensors, or combinations thereof. The docking station 106 at each of the workstations 104 may also include a memory 130 including a location identifier stored thereon. The location identifier identifies a location of the docking station 106 and the corresponding one of the workstations 104 within the workspace 102.
Decamp [0038] The system computer 138 is configured to receive the location identifier and sensor data from each docking station 106, and store this information in one or more databases.
Decamp [0040], [0055] generally disclosing utilization, and therefore capture, of data from one time period to another (e.g., from day to day, from month to month, etc.).
Decamp [0057] The docking station 106 may further be connected to an IoT sensor pack 210, which in some embodiments may include the sensor 128 of FIG. 1. By way of non-limiting example, the IoT sensor pack 210 may include an under-desk mounted sensor box including multiple data capture sensors (e.g., a thermal sensor, an infrared sensor, a motion sensor, an ambient temperature sensor, a humidity sensor, a pressure sensor, etc.). As a specific, non-limiting example, the IoT sensor pack 210 may include thermal, humidity, and pressure sensors to monitor ambient temperature, humidity, and pressure, respectively, at the workstation 104 and generate sensor data relating to the ambient temperature, humidity, and pressure.
analyze the received workspace data to determine workspace characteristics data, wherein the workspace characteristics data comprises: physical space data related to physical features in the workspace (e.g. map, ambient temperature, humidity, etc.); work mode data related to types of work performed by users in the workspace (e.g., map assigned work spaces, flexible occupancy, etc.); and user data related to individual users working in the workspace (e.g., map employee locations, user UI utilization, etc.);
Decamp [0030] generating a management dashboard with visual heat-mapping (e.g., a graphical user dashboard visualizes complex data using heat-mapping and easy-to-understand charting to show real-time or historic snapshots, quickly understand high-level overview of workspaces or drill down into the detail with device-level granularity, etc.)
Decamp [0038] As the system computer 138 is provided with the location identifier and the sensor data relating to the user occupancy for each docking station 106, the system computer 138 has sufficient information to determine a location and occupancy of each of the workstations 104 in the workspace 102, which enables a variety of useful functions. For example, the system computer 138 may be configured to use the location identifier and sensor data to generate usage data indicating how the workstations 104 are used (e.g., FIGS. 7 and 11).
Decamp [0039] In some embodiments, the computer code for occupancy 126 may be configured to instruct the system computer 138 to generate an availability notice indicating one or more of the workstations 104 that are currently unoccupied by a user and the locations of the currently unoccupied workstations 104 (e.g., FIG. 7). In some embodiments, the computer code for scheduling 118 may be configured to generate a schedule of currently available workstations 104. In some embodiments, the computer code for scheduling 118 may be configured to analyze usage data and generate a usage report indicative of user occupancy at workstations and their corresponding locations. The usage data may be reported using UIs (e.g., of web browsers, software applications of mobile devices or computers, etc.), online reports, printed reports, emails, other reports, or combinations thereof.
Decamp [0040] In some embodiments, the computer code for scheduling 118 may be configured to instruct the system computer 138 to analyze the usage data and generate an anticipated availability schedule indicating future likelihood of available workstations 104 and their corresponding locations. The future likelihood of available workstations 104 may be determined based on past observations of availability of the workstations 104. By way of non-limiting example, there may be some correlation between use of the workstations 104 from one time period to another (e.g., from day to day, from month to month, etc.). Also by way of non-limiting example, seasonal trends may be observed in the availability of the workstations 104. These correlations and trends may be leveraged to predict future availability of the workstations 104.
Decamp [0044] As previously discussed, in some embodiments the sensor data received by the system computer 138 from each docking station 106 may be indicative of user occupancy at the corresponding one of the workstations 104. As a result, the system computer 138 may be configured to generate usage data that is based on the sensor data. For example, the computer code for scheduling 118 may be configured to instruct the system computer 138 to generate a schedule of users currently assigned to workstations 104 and the locations of the assigned workstations 104. As a result, the system computer 138 is capable of tracking locations of users. In a work environment where employees do not have workstations 104 assigned permanently for their use, this may enable users (e.g., other employees, IT professionals, administrators, managers, etc.) to locate employees within the workspace 102. By way of non-limiting example, a user management UI 1100 may be provided, as will be discussed in more detail below.
Decamp [0055] A dashboard may be provided by the system computer 138 (e.g., using the computer code for system management 124). Examples of UIs (e.g., of web pages and/or mobile applications) that are provided by the dashboard are illustrated in FIGS. 3-13. Also, heat-maps may be used to illustrate measured metrics throughout the workspace 102. For example, a total power consumption heat-map 604 (FIG. 6) may be provided to enable a user to easily and quickly view and understand how power consumption is distributed throughout the workspace 102 at varying levels of detail. Other metrics may be illustrated using heat-maps. For example, ambient temperature at the workstations 104 may be illustrated using a heat-map similar to that of FIG. 6 (e.g., using the computer code for thermal imaging 120). In some embodiments, the heat-maps provided by the system computer 138 may update based on new sensor data in real-time. In some embodiments, the heat-maps provided by the system computer 138 may be snapshots at particular points in time. In some embodiments, the system computer 138 may analyze the sensor data to generate a chart of heat-mapping over a time interval. In some embodiments, the system computer 138 is configured to analyze the sensor data and generate a UI with indication of electronic devices (e.g., peripherals, other devices, etc.) at the workstations 104.
Decamp [0059]-[0061] FIGS. 3-13 generally disclosing how information can be displayed and manipulated, see below.
generate layout data based on the workspace characteristic data, wherein the layout data comprises positions for a plurality of work zones in the workspace and a target work mode for each work zone of the plurality of work zones; generate a visual output that provides the design specifications including positions for the plurality of work zones and the target work mode for each work zone in the workspace based on the generated layout data (fig. 6/7, map of consumption data, utilization data, occupancy trends in multiple zones/regions/floors/etc.);
Decamp [0059] FIGS. 3-13 are views of various example graphical user interfaces (UIs) 300, 400, 700, 800, 1100, and 1200 that may be provided by the system computer 138 of FIG. 1. These UIs include a main dashboard UI 300 (FIG. 3), a reports UI 400 (FIGS. 4-6, 9, and 10), a command center UI 700 (FIG. 7), a firmware update UI 800, a user management UI 1100, and an alerts UI 1200.
Decamp [0061] The UIs 300, 400, 700, 800, 1100, and 1200 each also include a change data scope menu 328 configured to enable a user to select between analyzing data originating from the docking station 106 of each of the workstations 104 (FIG. 1) of all regions or one or more selected regions, all offices or one or more selected offices, all floors or one or more selected floors within a selected office or offices, and all zones or one or more selected zones of one or more selected floors, offices, or regions. As a result, the UIs 300, 400, 700, 800, 1100, and 1200 allow the user to narrow or broaden the data shown to fit the selected scope
Decamp [0072] FIG. 6 is an example view of the reports UI 400, according to some embodiments. FIG. 6 shows a heat-map field 602 including a total power consumption heat-map 604, which may be provided by the reports UI 400 responsive to a user selection of the power consumption report option within the reports field 406. The total power consumption heat-map 604 includes a map of at least a portion of the workspace 102 (FIG. 1) that shows the workstations 104 and includes circular heat indicators 606 of varying size to indicate a total amount of power consumed at each of the workstations 104. In the example shown in FIG. 6, a larger size of the circular heat indicators 606 indicates a higher total power consumed at the workstations 104 as opposed to a smaller size of the circular heat indicators 606, which indicates a lower total power consumed at the workstations 104. The heat-map field 602 enables the user to graphically view areas within the workspace 102 where more or less power is consumed at the workstations 104, which may give an accurate idea of workstations 104 that are not being used (e.g., because less desirability of location, poor functioning of equipment, etc.) and workstations 104 that are being used improperly (e.g., where too much power is being used, which may indicate malfunctioning of equipment or use of unauthorized devices).
Decamp [0074] It should also be noted that heat-maps may be used herein to illustrate metrics other than total power consumed. For example, heat-maps may be used to illustrate time of occupancy of the workstations 104, temperature at the workstations 104, humidity at the workstations 104, battery charge of backup batteries at the workstations 104, other metrics, or combinations thereof.
Decamp [0075] FIG. 7 is an example view of the command center UI 700, according to some embodiments. The command center UI 700 is configured to indicate workstation configurations for a selected area (e.g., selected using the change data scope menu 328). The command center UI 700 includes a workstation configuration field 706 configured to provide workstation configuration information. The command center UI 700 also includes a map view option 702 and a list view option 704 configured to cause the workstation configuration field 706 to present the workstation configuration information in a map form and a list form, respectively, when selected by the user. In the example of FIG. 7, the map view option 702 is selected, so the workstation configuration field 706 is shown in the map form, including a map of the selected portion of the workspace 102. The workstations 104 of the selected portion of the workspace 102 are shown in the workstation configuration field 706.
receive new workspace data for a new time period after the first time period (e.g., periods of time, such as day, month and season); and generate at least one update for the generated visual output based on the new workspace data (e.g., tre).
Decamp [0040] In some embodiments, the computer code for scheduling 118 may be configured to instruct the system computer 138 to analyze the usage data and generate an anticipated availability schedule indicating future likelihood of available workstations 104 and their corresponding locations. The future likelihood of available workstations 104 may be determined based on past observations of availability of the workstations 104. By way of non-limiting example, there may be some correlation between use of the workstations 104 from one time period to another (e.g., from day to day, from month to month, etc.). Also by way of non-limiting example, seasonal trends may be observed in the availability of the workstations 104. These correlations and trends may be leveraged to predict future availability of the workstations 104.
Decamp [0041] The ability to monitor and/or predict use of the workstations 104 may enable more efficient use of office space, equipment, and power. For example, if it is determined that fewer workstations 104 are needed to accommodate the demand for workstations 104, savings may be made by reducing real estate, equipment, and/or electrical power costs. Also, the ability to monitor and/or predict use of the workstations 104 may enable planning ahead for increased demand for workstations 104 rather than be left with insufficient workstations 104 once it is realized that more workstations 104 are needed while additional real estate and/or equipment is/are acquired. See also [0044]
Decamp [0030], [0055], [0072], [0074], [0075] generating a management dashboard with visual heat-mapping (e.g., a graphical user dashboard visualizes complex data using heat-mapping and easy-to-understand charting to show real-time or historic snapshots, quickly understand high-level overview of workspaces or drill down into the detail with device-level granularity, etc.)
Regarding claim 3, Decamp further discloses the limitations of claim 1, and further discloses: wherein a work mode for a work zone is at least one of a a dedicated user desk, an unassigned user desk, an activity-based desk used by a plurality of users, a sitting desk, and a standing desk.
Decamp [0016] Embodiments disclosed herein enable monitoring of how assets at a workspace (e.g., desks, workstations, etc.) are being used (e.g., which assets are being used most) and determining why or why not the assets are being used… embodiments disclosed herein enable determining whether a workspace including 2,000 (e.g., each including a desk) workstations is being effectively used, or if a smaller, cheaper workspace including only 1,400 workstations would be sufficient. Downscaling to a smaller number of workstations could reduce costs significantly by reducing the amount of money spent on real estate, furnishings for the workspace, and power consumption.
Decamp [0025] managing workspace occupancy and scheduling (e.g., provide workspace utilization data, schedule Hotdesking environments where users are not permanently assigned to particular workstations 104, understand how a flexible workspace is working, maximize available space, reduce real estate costs, etc.)
Decamp [0040] In some embodiments, the computer code for scheduling 118 may be configured to instruct the system computer 138 to analyze the usage data and generate an anticipated availability schedule indicating future likelihood of available workstations 104 and their corresponding locations. The future likelihood of available workstations 104 may be determined based on past observations of availability of the workstations 104. By way of non-limiting example, there may be some correlation between use of the workstations 104 from one time period to another (e.g., from day to day, from month to month, etc.). Also by way of non-limiting example, seasonal trends may be observed in the availability of the workstations 104. These correlations and trends may be leveraged to predict future availability of the workstations 104.
Decamp [0041] The ability to monitor and/or predict use of the workstations 104 may enable more efficient use of office space, equipment, and power. For example, if it is determined that fewer workstations 104 are needed to accommodate the demand for workstations 104, savings may be made by reducing real estate, equipment, and/or electrical power costs. Also, the ability to monitor and/or predict use of the workstations 104 may enable planning ahead for increased demand for workstations 104 rather than be left with insufficient workstations 104 once it is realized that more workstations 104 are needed while additional real estate and/or equipment is/are acquired.
Decamp [0044] As previously discussed, in some embodiments the sensor data received by the system computer 138 from each docking station 106 may be indicative of user occupancy at the corresponding one of the workstations 104. As a result, the system computer 138 may be configured to generate usage data that is based on the sensor data. For example, the computer code for scheduling 118 may be configured to instruct the system computer 138 to generate a schedule of users currently assigned to workstations 104 and the locations of the assigned workstations 104. As a result, the system computer 138 is capable of tracking locations of users. In a work environment where employees do not have workstations 104 assigned permanently for their use, this may enable users (e.g., other employees, IT professionals, administrators, managers, etc.) to locate employees within the workspace 102. By way of non-limiting example, a user management UI 1100 may be provided, as will be discussed in more detail below. If irregularities are detected in the finding employees, or if unauthorized users are located, alerts may be generated (e.g., see FIGS. 12-13).
Decamp [0069] The top power consuming workstations field 410 is configured to indicate the top power consuming workstations 104 (FIG. 1) (e.g., in order from top power consuming to least power consuming), a total power consumed by these workstations 104, how much of the total power was consumed from an outlet of the docking station 106 (FIGS. 1 and 2) and various power outlets of the smart power 202 (FIG. 2) (e.g., GPO1, GPO2, GPO3, etc.), which office, floor, and zone the workstations 104 are located in, and which user or users the workstations 104 were assigned to. The top power consuming workstations field 410 may also provide a search bar to enable the user to search for a specific one of the workstations 104 to gather the power consumption information regarding the specific one of the workstations 104.
Regarding claim 4, Decamp discloses the limitations of claim 1 and further discloses: wherein updating the generated visual output further comprises: monitoring a metric related to a particular objective, wherein the objective is at least one of workspace utilization, occupancy, and user satisfaction (e.g., consumption of power, occupancy and scheduling, access/security, etc.); and updating the generated visual output when the metric fails to satisfy a criteria (e.g., alerts).
Decamp [0016] Embodiments disclosed herein enable monitoring of how assets at a workspace (e.g., desks, workstations, etc.) are being used (e.g., which assets are being used most) and determining why or why not the assets are being used… embodiments disclosed herein enable determining whether a workspace including 2,000 (e.g., each including a desk) workstations is being effectively used, or if a smaller, cheaper workspace including only 1,400 workstations would be sufficient. Downscaling to a smaller number of workstations could reduce costs significantly by reducing the amount of money spent on real estate, furnishings for the workspace, and power consumption.
Decamp [0023] The system network interface 116 of the system computer 138 and the network interface 112 of each docking station 106 enables the system computer 138 to manage the workspace 102 in a variety of ways. For example, the system computer 138 may be capable of: [0024] managing and monitoring consumption of power at the workstations 104 (e.g., capturing and analyzing individual device power consumption at the workstations 104, understand and optimize power consumption at the workstations 104, schedule power on/off events, etc.) [0025] managing workspace occupancy and scheduling (e.g., provide workspace utilization data, schedule Hotdesking environments where users are not permanently assigned to particular workstations 104, understand how a flexible workspace is working, maximize available space, reduce real estate costs, etc.). [0026] managing access and/or security of workstations through authentication tools such as radio frequency identification (RFID) (e.g., near field communication, or “NFC”). [0027] managing assets (e.g., automatic identification and inventorying of peripheral devices connected to docking stations 106, etc.) [0028] managing and actuating devices remotely (e.g., enable IT professionals to remotely manage the workspace 102, perform soft resets, power cycle, and firmware updates remotely, etc.) [0029] securing workspace and finding employees (e.g., identify and locate employees based on their scheduled workstations 104, provide enhanced network security, understand which of the workstations 104 employees are located in, enable employees to find each other, and enable employees to work more efficiently and securely, etc.
Decamp [0088] FIG. 12 is an example view of the alerts UI 1200, according to some embodiments. The alerts UI 1200 is configured to enable a user to view and take actions on alerts affecting the system 100 of FIG. 1. The alerts may include critical alerts (e.g., alerts regarding communication connectivity loss, internal temperature of the workspace 102, escalated alerts, etc.), warnings (e.g., battery level (of a sensor battery), power consumption, usage duration, unauthorized access, ambient sensor threshold warnings, etc.), and notifications (e.g., new update notifications, override event notifications, etc.). The alerts UI 1200 includes an alerts display field 1214 configured to display alerts for a selected area (e.g., selected using the change data scope menu 328).
Decamp [0089] The alerts displayed in the alerts display field 1214 may be displayed in a map view responsive to a user selection of a map view option 1208 (as illustrated in FIG. 12) or in a list view responsive to a user selection of a list view option 1210 (as illustrated in FIG. 13). In the map view, the alerts display field 1214 may be configured to display alert links 1212 at locations within the workspace 102 where issues associated with the alerts are located. These alert links 1212, if selected by a user, may navigate to UIs designed to enable the user to take action on the specific issues associated with the alerts or escalate the alerts (e.g., to critical alerts).
Regarding claim 5, Decamp discloses the limitations of claim 1 and further discloses: wherein the set of sensors comprises at least one of a motion sensor, an image sensor, a user flow sensor, a time-of-flight sensor, an infrared (IR) based sensor, an ultrasonic sensor, a thermal sensor, a Carbon dioxide (CO2) sensor, a vibration sensor, an air quality sensor, a temperature sensor, a humidity sensor, a light sensor, and an audio sensor.
Decamp [0036] The docking station 106 at each of the workstations 104 of the workspace 102 may include a sensor 128 to monitor user occupancy at the corresponding one of the workstations 104 and generate sensor data relating to the user occupancy. By way of non-limiting example, the sensor 128 may include an infrared sensor and/or thermal sensor to confirm user occupancy. A thermal sensor may be configured to monitor ambient temperature at the corresponding one of the workstations 104 and generate sensor data relating to the ambient temperature. Other examples of the sensor 128 may include a temperature sensor, a humidity sensor, a power use sensor (e.g., to sense when power is being drawn from the docking station 106 and/or other power supplies at the workstations 104), an image sensor (e.g., a camera), a motion sensor, a capacitive sensor, a mechanical sensor (e.g., in a chair), a radio frequency identification (RFID) sensor (e.g., to detect an RFID signature produced by a device such as an NFC device carried by the user and/or the computer device 132), a battery charge sensor of a battery that powers the sensor 128 or the IoT sensor pack 210 of FIG. 2, other sensors, or combinations thereof. The docking station 106 at each of the workstations 104 may also include a memory 130 including a location identifier stored thereon. The location identifier identifies a location of the docking station 106 and the corresponding one of the workstations 104 within the workspace 102.
Regarding claim 7, Decamp discloses the limitations of claim 1 and further discloses: wherein the visual output comprises at least one of a visual floor plan, a 3D rendering of a layout, and instructions to modify a layout.
Decamp [0023] The system network interface 116 of the system computer 138 and the network interface 112 of each docking station 106 enables the system computer 138 to manage the workspace 102 in a variety of ways. For example, the system computer 138 may be capable of: [0024] managing and monitoring consumption of power at the workstations 104 (e.g., capturing and analyzing individual device power consumption at the workstations 104, understand and optimize power consumption at the workstations 104, schedule power on/off events, etc.) [0025] managing workspace occupancy and scheduling (e.g., provide workspace utilization data, schedule Hotdesking environments where users are not permanently assigned to particular workstations 104, understand how a flexible workspace is working, maximize available space, reduce real estate costs, etc.). [0026] managing access and/or security of workstations through authentication tools such as radio frequency identification (RFID) (e.g., near field communication, or “NFC”). [0027] managing assets (e.g., automatic identification and inventorying of peripheral devices connected to docking stations 106, etc.) … [0030] generating a management dashboard with visual heat-mapping (e.g., a graphical user dashboard visualizes complex data using heat-mapping and easy-to-understand charting to show real-time or historic snapshots, quickly understand high-level overview of workspaces or drill down into the detail with device-level granularity, etc.)
Decamp [0040] In some embodiments, the computer code for scheduling 118 may be configured to instruct the system computer 138 to analyze the usage data and generate an anticipated availability schedule indicating future likelihood of available workstations 104 and their corresponding locations. The future likelihood of available workstations 104 may be determined based on past observations of availability of the workstations 104. By way of non-limiting example, there may be some correlation between use of the workstations 104 from one time period to another (e.g., from day to day, from month to month, etc.). Also by way of non-limiting example, seasonal trends may be observed in the availability of the workstations 104. These correlations and trends may be leveraged to predict future availability of the workstations 104.
Decamp [0041] The ability to monitor and/or predict use of the workstations 104 may enable more efficient use of office space, equipment, and power. For example, if it is determined that fewer workstations 104 are needed to accommodate the demand for workstations 104, savings may be made by reducing real estate, equipment, and/or electrical power costs. Also, the ability to monitor and/or predict use of the workstations 104 may enable planning ahead for increased demand for workstations 104 rather than be left with insufficient workstations 104 once it is realized that more workstations 104 are needed while additional real estate and/or equipment is/are acquired.
Decamp [0059] FIGS. 3-13 are views of various example graphical user interfaces (UIs) 300, 400, 700, 800, 1100, and 1200 that may be provided by the system computer 138 of FIG. 1. These UIs include a main dashboard UI 300 (FIG. 3), a reports UI 400 (FIGS. 4-6, 9, and 10), a command center UI 700 (FIG. 7), a firmware update UI 800, a user management UI 1100, and an alerts UI 1200.
Decamp [0075] FIG. 7 is an example view of the command center UI 700, according to some embodiments. The command center UI 700 is configured to indicate workstation configurations for a selected area (e.g., selected using the change data scope menu 328). The command center UI 700 includes a workstation configuration field 706 configured to provide workstation configuration information. The command center UI 700 also includes a map view option 702 and a list view option 704 configured to cause the workstation configuration field 706 to present the workstation configuration information in a map form and a list form, respectively, when selected by the user. In the example of FIG. 7, the map view option 702 is selected, so the workstation configuration field 706 is shown in the map form, including a map of the selected portion of the workspace 102. The workstations 104 of the selected portion of the workspace 102 are shown in the workstation configuration field 706.
Decamp [0030], [0055], [0072], [0074], [0075] generating a management dashboard with visual heat-mapping (e.g., a graphical user dashboard visualizes complex data using heat-mapping and easy-to-understand charting to show real-time or historic snapshots, quickly understand high-level overview of workspaces or drill down into the detail with device-level granularity, etc.)
Regarding claim 9, Decamp discloses the limitations of claim 1 and further discloses: wherein generating layout data based on the space characteristic data comprises performing at least one optimization process with respect to an objective, wherein the objective is at least one of cost, workspace utilization, occupancy, user satisfaction, and productivity.
Decamp [0016] Embodiments disclosed herein enable monitoring of how assets at a workspace (e.g., desks, workstations, etc.) are being used (e.g., which assets are being used most) and determining why or why not the assets are being used. By way of specific, non-limiting example, embodiments disclosed herein enable determining whether a workspace including 2,000 (e.g., each including a desk) workstations is being effectively used, or if a smaller, cheaper workspace including only 1,400 workstations would be sufficient.
Decamp [0023] The system network interface 116 of the system computer 138 and the network interface 112 of each docking station 106 enables the system computer 138 to manage the workspace 102 in a variety of ways. For example, the system computer 138 may be capable of: [0024] managing and monitoring consumption of power at the workstations 104 (e.g., capturing and analyzing individual device power consumption at the workstations 104, understand and optimize power consumption at the workstations 104, schedule power on/off events, etc.) [0025] managing workspace occupancy and scheduling (e.g., provide workspace utilization data, schedule Hotdesking environments where users are not permanently assigned to particular workstations 104, understand how a flexible workspace is working, maximize available space, reduce real estate costs, etc.).
Decamp [0040] In some embodiments, the computer code for scheduling 118 may be configured to instruct the system computer 138 to analyze the usage data and generate an anticipated availability schedule indicating future likelihood of available workstations 104 and their corresponding locations. The future likelihood of available workstations 104 may be determined based on past observations of availability of the workstations 104. By way of non-limiting example, there may be some correlation between use of the workstations 104 from one time period to another (e.g., from day to day, from month to month, etc.). Also by way of non-limiting example, seasonal trends may be observed in the availability of the workstations 104. These correlations and trends may be leveraged to predict future availability of the workstations 104.
Decamp [0041] The ability to monitor and/or predict use of the workstations 104 may enable more efficient use of office space, equipment, and power. For example, if it is determined that fewer workstations 104 are needed to accommodate the demand for workstations 104, savings may be made by reducing real estate, equipment, and/or electrical power costs. Also, the ability to monitor and/or predict use of the workstations 104 may enable planning ahead for increased demand for workstations 104 rather than be left with insufficient workstations 104 once it is realized that more workstations 104 are needed while additional real estate and/or equipment is/are acquired.
Regarding claims 10 and 11, the limitations of claims 10 and 11 are analogous to the limitations of claim 1. See the rejection of claim 1 above.
Regarding claim 13, the limitations of claim 13 are analogous to the limitations of claim 3. See the rejection of claim 3 above.
Regarding claim 14, the limitations of claim 14 are analogous to the limitations of claim 4. See the rejection of claim 4 above.
Regarding claim 15, the limitations of claim 15 are analogous to the limitations of claim 5. See the rejection of claim 5 above.
Regarding claim 17, the limitations of claim 17 are analogous to the limitations of claim 7. See the rejection of claim 7 above.
Regarding claim 19, the limitations of claim 19 are analogous to the limitations of claim 9. See the rejection of claim 9 above.
Claim Rejections - 35 USC § 103
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.
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) 2 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Decamp et al. (US 20200219036) in view of Florez Choque et al. (US 20200234178).
Regarding claim 2, Decamp, as shown above, discloses the limitations of claim 1. Decamp discloses processing the received space data (see rejection of claim 1), but does not disclose the application of a neural network in the analysis thereof.
Florez Choque is directed to a system and method for learning design policies. Florez Choque discloses: processing the received space data using a neural network, wherein the neural network is trained on a training dataset that includes layout data.
Florez Choque [0012] Embodiments disclosed herein represent a problem as a task (also referred to as a goal), and a sequential solution as the sequential instantiation of a policy, with the desired outcome to find the optimal policy (or sequence of actions) to complete a task in an environment (e.g., a real-world environment such as a bank, …, etc.). For example, the task may specify to … design the optimal layout of offices and personnel in a physical …location.
Florez Choque [0019] As shown, the computing system 101 includes a policy generator 110, story generator 111, environment component 112, a machine learning (ML) algorithm 113, a data store of training data 114, a data store of input data 115, a data store of ML models 116, and a data store of story data 117. The policy generator 110 learns policies that include an optimal sequence of actions that can be used to complete a task in a real-world environment and/or a computing environment. A task may include any number and type of desired objectives, such as achieving customer satisfaction, improving the performance of a computing system and/or computing application, completion of a task, improving a workflow, a goal, receiving positive reviews from customers, receiving bank deposits, opening new customer accounts, designing workflows, designing retail locations, staffing retail locations, designing user interfaces (UIs) for applications, etc. In at least one embodiment, users may define one or more tasks.
Florez Choque [0020] The policy generator 110 learns such policies based on the ML algorithm 113 (which may be an artificial neural network (ANN) algorithm) and the training data 114 during a training phase associated with completion of a task. The training data 114 includes any number and type of data, such as user actions, user interactions, audio data, video data, image data, text data, and data generated by applications.
One of ordinary skill in the art at the time of filing would have recognized that applying the known technique of Florez Choque to Decamp would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the learning technique of Florez Choque to the optimization analysis of Decamp would have yielded predictable results and resulted in an improved system that would allow more efficient layout optimization that facilitates task completion in a workspace.
Regarding claim 12, the limitations of claim 12 are analogous to the limitations of claim 2. See the rejection of claim 2 above.
Claim(s) 6, 8, 16 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Decamp et al. (US 20200219036) in view of Park et al. (US 20190158309)
Regarding claim 6, Decamp discloses the limitations of claim 1 and further discloses: wherein the space data further comprises … data related to feedback from individuals working within the space (e.g., workspace utilization, occupancy, scheduling, etc.), environmental data related to environmental conditions in the space (e.g. temperature, humidity, etc.).
Decamp [0023] The system 100 also includes a system computer 138 including a system network interface 116 to enable the system computer 138 to communicate, through the network 114, with each docking station 106 at each of the plurality of workstations 104. The system computer 138 may include one or more computer devices located on-site at the workspace 102, off-site, in a cloud network (e.g., the cloud with analytics/in house server 214 of FIG. 2), in an in-house network (e.g., the in-house IT network 218 of FIG. 2), or combinations thereof. The system network interface 116 of the system computer 138 and the network interface 112 of each docking station 106 enables the system computer 138 to manage the workspace 102 in a variety of ways. For example, the system computer 138 may be capable of: [0024] managing and monitoring consumption of power at the workstations 104 (e.g., capturing and analyzing individual device power consumption at the workstations 104, understand and optimize power consumption at the workstations 104, schedule power on/off events, etc.) [0025] managing workspace occupancy and scheduling (e.g., provide workspace utilization data, schedule Hotdesking environments where users are not permanently assigned to particular workstations 104, understand how a flexible workspace is working, maximize available space, reduce real estate costs, etc.). [0026] managing access and/or security of workstations through authentication tools such as radio frequency identification (RFID) (e.g., near field communication, or “NFC”). [0027] managing assets (e.g., automatic identification and inventorying of peripheral devices connected to docking stations 106, etc.) [0028] managing and actuating devices remotely (e.g., enable IT professionals to remotely manage the workspace 102, perform soft resets, power cycle, and firmware updates remotely, etc.) [0029] securing workspace and finding employees (e.g., identify and locate employees based on their scheduled workstations 104, provide enhanced network security, understand which of the workstations 104 employees are located in, enable employees to find each other, and enable employees to work more efficiently and securely, etc.) [0030] generating a management dashboard with visual heat-mapping (e.g., a graphical user dashboard visualizes complex data using heat-mapping and easy-to-understand charting to show real-time or historic snapshots, quickly understand high-level overview of workspaces or drill down into the detail with device-level granularity, etc.)
Decamp [0074] It should also be noted that heat-maps may be used herein to illustrate metrics other than total power consumed. For example, heat-maps may be used to illustrate time of occupancy of the workstations 104, temperature at the workstations 104, humidity at the workstations 104, battery charge of backup batteries at the workstations 104, other metrics, or combinations thereof.
Decamp [0075] FIG. 7
While Decamp discloses the collection of user information for space planning, but the information that is collected may or may not be interpreted as feedback from a user.
Park is directed to a system for building management. Park more explicitly discloses user feedback being used in the consideration of environmental factors (e.g., policy determinations/updates made for optimal user comfort).
Park [0200] FIG. 5 is a block diagram of a building management system (BMS) which can be used to monitor and control building 10.
Park [0205] AHU 206 may receive input from sensors located within AHU 206 and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow through AHU 206 to achieve setpoint conditions for the building zone.
Park [0233] Enterprise integration layer 510 can be configured to serve clients or local applications with information and services to support a variety of enterprise-level applications. For example, enterprise control applications 526 can be configured to provide subsystem-spanning control to a graphical user interface (GUI) or to any number of enterprise-level business applications (e.g., accounting systems, user identification systems, etc.). Enterprise control applications 526 may also or alternatively be configured to provide configuration GUIs for configuring BMS controller 466. In yet other embodiments, enterprise control applications 526 can work with layers 510-520 to improve and/or optimize building performance (e.g., efficiency, energy use, comfort, or safety) based on inputs received at interface 507 and/or BMS interface 509.
Park [0235] Demand response layer 514 can be configured to determine (e.g., optimize) resource usage (e.g., electricity use, natural gas use, water use, etc.) and/or the monetary cost of such resource usage to satisfy the demand of building 10.
Park [0238] Demand response layer 514 may further include or draw upon one or more demand response policy definitions (e.g., databases, XML files, etc.). The policy definitions can be edited or adjusted by a user (e.g., via a graphical user interface) so that the control actions initiated in response to demand inputs can be tailored for the user's application, desired comfort level, particular building equipment, or based on other concerns. For example, the demand response policy definitions can specify which equipment can be turned on or off in response to particular demand inputs, how long a system or piece of equipment should be turned off, what setpoints can be changed, what the allowable set point adjustment range is, how long to hold a high demand setpoint before returning to a normally scheduled setpoint, how close to approach capacity limits, which equipment modes to utilize, the energy transfer rates (e.g., the maximum rate, an alarm rate, other rate boundary information, etc.) into and out of energy storage devices (e.g., thermal storage tanks, battery banks, etc.), and when to dispatch on-site generation of energy (e.g., via fuel cells, a motor generator set, etc.).
One of ordinary skill in the art at the time of filing would have recognized that applying the known technique of Park to Decamp would have yielded predictable results and resulted in an improved system because the level of ordinary skill in the art demonstrated by the references applied shows the ability to facilitate control functions through the acquisition of workspace data. Further, applying additional building control functions, including user policy considerations, of Park to the monitoring system of Decamp would have been recognized by one of ordinary skill in the art at the time of tiling as resulting in an improved system that would allow for environmental optimization.
Regarding claim 16, the limitations of claim 16 are analogous to the limitations of claim 6. See the rejection of claim 6 above.
Regarding claim 8, Decamp discloses the limitations of claim 1 and further discloses: wherein the adaptive layout generation application further directs the processor to output control signals to modify … the space.
Decamp [0021] The embodiments disclosed herein may benefit docking station users, IT management and IT support personnel, facilities and space planners, and real estate and change management. For IT management and support personnel, the embodiments disclosed herein enable remote docking station reset (e.g., from the next room or from a continent away), remote docking station firmware updates, remote diagnostics (e.g., workstation health diagnostics), connected peripheral identification, and remote Alternating Current (AC) power on/off control and power event scheduling.
While Decamp discloses sending control signals in response to the analysis of received data, the control signals may or may not represent a modification of an “environment.”
Park is directed to a system for building management. Park discloses wherein the adaptive application further directs the processor to output control signals to modify an environment of the space.
Park [0200] FIG. 5 is a block diagram of a building management system (BMS) which can be used to monitor and control building 10.
Park [0205] AHU 206 may receive input from sensors located within AHU 206 and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow through AHU 206 to achieve setpoint conditions for the building zone.
Park [0233] Enterprise integration layer 510 can be configured to serve clients or local applications with information and services to support a variety of enterprise-level applications. For example, enterprise control applications 526 can be configured to provide subsystem-spanning control to a graphical user interface (GUI) or to any number of enterprise-level business applications (e.g., accounting systems, user identification systems, etc.). Enterprise control applications 526 may also or alternatively be configured to provide configuration GUIs for configuring BMS controller 466. In yet other embodiments, enterprise control applications 526 can work with layers 510-520 to improve and/or optimize building performance (e.g., efficiency, energy use, comfort, or safety) based on inputs received at interface 507 and/or BMS interface 509.
Park [0235] Demand response layer 514 can be configured to determine (e.g., optimize) resource usage (e.g., electricity use, natural gas use, water use, etc.) and/or the monetary cost of such resource usage to satisfy the demand of building 10.
Park [0238] Demand response layer 514 may further include or draw upon one or more demand response policy definitions (e.g., databases, XML files, etc.). The policy definitions can be edited or adjusted by a user (e.g., via a graphical user interface) so that the control actions initiated in response to demand inputs can be tailored for the user's application, desired comfort level, particular building equipment, or based on other concerns. For example, the demand response policy definitions can specify which equipment can be turned on or off in response to particular demand inputs, how long a system or piece of equipment should be turned off, what setpoints can be changed, what the allowable set point adjustment range is, how long to hold a high demand setpoint before returning to a normally scheduled setpoint, how close to approach capacity limits, which equipment modes to utilize, the energy transfer rates (e.g., the maximum rate, an alarm rate, other rate boundary information, etc.) into and out of energy storage devices (e.g., thermal storage tanks, battery banks, etc.), and when to dispatch on-site generation of energy (e.g., via fuel cells, a motor generator set, etc.).
One of ordinary skill in the art at the time of filing would have recognized that applying the known technique of Park to Decamp would have yielded predictable results and resulted in an improved system because the level of ordinary skill in the art demonstrated by the references applied shows the ability to facilitate control functions through the acquisition of workspace data. Further, applying additional building control functions of Park to the monitoring system of Decamp would have been recognized by one of ordinary skill in the art at the time of tiling as resulting in an improved system that would allow more efficient layout optimization.
Regarding claim 18, the limitations of claim 18 are analogous to the limitations of claim 8. See the rejection of claim 8 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kurtzberg et al. (20050182636 A1), directed to adaptive analysis techniques for planning office layout
Amigo et al. (US 20170109829 A1), directed to a workplace activity evaluator
Srebric et al. (US 20210068673 A1), directed to occupant monitoring for building office management
Srivastava et al. (US 20190188338 A1), directed to workspace environment design and build
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABBY J FLYNN whose telephone number is (571)272-9855. The examiner can normally be reached Monday - Friday 8:30-5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, James Trammell can be reached at 571-272-6712. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ABBY J FLYNN/Primary Patent Examiner, Art Unit 3663