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Patent Application 18313552 - VEHICLE SENSORS FOR OBSERVATION OF SURROUNDING - Rejection

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Patent Application 18313552 - VEHICLE SENSORS FOR OBSERVATION OF SURROUNDING

Title: VEHICLE SENSORS FOR OBSERVATION OF SURROUNDING FLEET VEHICLES

Application Information

  • Invention Title: VEHICLE SENSORS FOR OBSERVATION OF SURROUNDING FLEET VEHICLES
  • Application Number: 18313552
  • Submission Date: 2025-05-20T00:00:00.000Z
  • Effective Filing Date: 2023-05-08T00:00:00.000Z
  • Filing Date: 2023-05-08T00:00:00.000Z
  • National Class: 701
  • National Sub-Class: 002000
  • Examiner Employee Number: 95822
  • Art Unit: 3667
  • Tech Center: 3600

Rejection Summary

  • 102 Rejections: 0
  • 103 Rejections: 1

Cited Patents

No patents were cited in this rejection.

Office Action Text


    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 .

Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/08/2023 is in compliance with the provisions of 37 CFR 1.97.  Accordingly, the information disclosure statement is being considered by the examiner.

Claim Objections
Claims 1, 13, and 15 are objected to because of the following informalities: 
Claim 1 contains an unpaired end bracket in line 2. 
Claims 13 and 15 are identical. They contain identical limitations and both depend from Claim 8. 
Appropriate correction is required.

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 8-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. 
101 Analysis – Step 1 
Claim 8 is directed to a system for fleet parking area surveillance. Therefore, Claim 8 within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I 
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. 
Claim 8 recites: 
A system for fleet parking area surveillance, comprising: 
a plurality of vehicles in communication with a dispatch service, each vehicle having a respective sensor suite including a plurality of image sensors, wherein each of the plurality of image sensors is configured to capture an image upon vehicle parking in a respective parking space in a parking area; 
a dispatch service in communication with each of the plurality of vehicles and configured to dispatch respective vehicles to the parking area; 
a central computer in communication with the dispatch service and with each of the plurality of vehicles, the central computer configured to: 
receive captured images from each of the plurality of image sensors from each respective vehicle of the plurality of vehicles, 
store the received captured images as a set of available captured images, 
process the set of available captured images to identify a respective field of view of the parking area corresponding to each of the set of available captured images, 
identify a subset of the set of available captured images that together provide a selected field of view of the parking area, and 
identify a subset of the plurality of vehicles corresponding to the identified subset of the available captured images.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, processing and identifying all the various data in the context of this claim encompasses a person looking at data collected (obtained, received, etc.) and forming a simple judgement (determination, analysis, comparison, etc.) either mentally or using a pen and paper. Accordingly, the claim recites at least one abstract idea. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that  "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). 
101 Analysis – Step 2A, Prong II 
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” 
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”): 
A system for fleet parking area surveillance, comprising: 
a plurality of vehicles in communication with a dispatch service, each vehicle having a respective sensor suite including a plurality of image sensors, wherein each of the plurality of image sensors is configured to capture an image upon vehicle parking in a respective parking space in a parking area; 
a dispatch service in communication with each of the plurality of vehicles and configured to dispatch respective vehicles to the parking area; 
a central computer in communication with the dispatch service and with each of the plurality of vehicles, the central computer configured to: 
receive captured images from each of the plurality of image sensors from each respective vehicle of the plurality of vehicles, 
store the received captured images as a set of available captured images, 
process the set of available captured images to identify a respective field of view of the parking area corresponding to each of the set of available captured images, 
identify a subset of the set of available captured images that together provide a selected field of view of the parking area, and 
identify a subset of the plurality of vehicles corresponding to the identified subset of the available captured images.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application. 
Regarding the additional limitations above, the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (processor) to perform the process. In particular, the steps of receiving and storing the captured images is recited at a high level of generality (i.e. as a general means of receiving information and casting rays to detect information for use in the determining and other steps), and amounts to no more than mere data gathering necessary to perform the abstract idea, which is a form of insignificant extra-solution activity. Claim 8 further recites a plurality of vehicles, a dispatch service, a plurality of image sensors, and a central computer. These limitations merely describe how to generally “apply” the otherwise mental judgements in a generic or general purpose vehicle control environment. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). The device(s) and processor(s) are recited at a high level of generality and merely automates the steps. 
***In order to expedite prosecution, Examiner also notes that the mere recitation of “a dispatch service… configured to dispatch respective vehicles to the parking area” in Claim 8 is not significant enough to integrate the judicial exception into a practical application since the claims do not include a positive recitation of “dispatching respective vehicles to the parking area”, as seen in Claim 1.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. 
101 Analysis – Step 2B 
Regarding Step 2B of the 2019 PEG, representative independent claim 9 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the steps amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using generic computer components cannot provide an inventive concept. And as discussed above, the additional limitations discussed above are insignificant extra-solution activities. 
The additional limitations of receiving and storing information are well-understood, routine and conventional activities because the specification does not provide any indication that the sensors are anything other than a conventional vehicle sensors. 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.  
Dependent Claims 9-14 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent Claims 9-14 are not patent eligible under the same rationale as provided for in the rejection of Claim m8. 
Therefore, Claims 8-15 are ineligible under 35 USC §101.

Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.

The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 20240005792 A1, filed 06/29/2022, hereinafter “Muehl”, in view of US 20210354689 A1, with an earliest priority date of 05/15/2020, hereinafter “Schreiber”, further in view of “Energy Saving Strategy for Video-based Wireless Sensor Networks Under Field Coverage Preservation”, published May 2008, hereinafter “Pescaru”.
Regarding Claim 1, Muehl teaches a computer implemented method for vehicle fleet surveillance. See at least figures 10-15, processor 1010.
comprising: a plurality of vehicles from a vehicle fleet to parking spaces in a parking area. See at least [0045]-[0046] and figure 3, wherein a plurality of vehicles 326 are located in a parking area 322. Additionally, see at least [0002] and [0046], wherein multiple vehicles are under control/ownership of a fleet operator.
wherein each of the plurality of vehicles includes a respective sensor suite having a plurality of image sensors. See at least [0026], [0044] and figure 2, wherein each vehicle includes a sensor suite including sensors 210-216. The sensors can comprise different types of cameras which provide image data. 
receiving captured images from each of the plurality of image sensors from each respective vehicle of the plurality of vehicles and storing the received captured images as a set of available captured images. See at least [0026], wherein sensor data including image and video data is received from sensors of the vehicle. Additionally, see at least [0054]-[0055] and figures 6-7, wherein the sensor data is stored in a data structure as a set of available sensor data.
determining that each vehicle in the subset of vehicles has sufficient charge to support sentinel mode operation. See at least [0029], wherein a determination is made that each of the vehicles have sufficient power to support the vehicles’ actions. The actions can include activating particular sensors of the vehicles.
and transmitting a message to each vehicle in the subset of vehicles to activate the respective sensor suites and enter sentinel mode operation. See at least [0062]-[0064] and figure 11, wherein a transmission is initiated to activate a guard mode to each of the vehicles in a subset of vehicles (first and second vehicle). Activating guard mode comprises recording sensor data by the sensors of each vehicle and transmitting the sensor data.
Muehl remains silent on dispatching, by a central computer; processing the set of available captured images to identify a respective field of view of the parking area corresponding to each of the set of available captured images; identifying a subset of the set of available captured images that together provide a selected field of view of the parking area; identifying a subset of the plurality of vehicles corresponding to the identified subset of captured images. As discussed above, Muehl (see figure 3) teaches identifying a subset of vehicles including a first and second vehicle 326 from the plurality of vehicles, but does not specify how the subset is identified.
Schreiber teaches dispatching, by a central computer. See at least [0057]-[0060], wherein vehicles are autonomously dispatched to recommended parking spots by an external cloud computer.
processing the set of available captured images to identify a respective field of view of the parking area corresponding to each of the set of available captured images. See at least [0073], [0084]-[0087], [0099], and figure 3, step M2, wherein an individual sensing coverage is identified based on the received parking data from the plurality of vehicles. The individual sensing coverage for a vehicle represents the field of view of the associated sensor of that particular vehicle.
identifying a subset of the set of available captured images that together provide a selected field of view of the parking area. See at least [0089]-[0095], figure 3, step M3, and figures 11-16, wherein a coverage ratio is calculated, representing the subset of individual sensing coverages 8 (set of available captured images) that together provide a selected field of view of the parking area.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of dispatching vehicles by a central computer, identifying a respective field of view of the parking area from the set of available captured images, and identifying a subset of the set of available captured images that together provide a selected field of view of the parking area. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Pescaru teaches identifying a subset of the plurality of vehicles corresponding to the identified subset of captured images. See at least pg. 3, left column, and figure 1, wherein a set of captured image data is processed to identify and deploy a plurality of sensors that together provide a selected field of view of a target surface. See at least pg. 3, right column and page 5, left column, wherein, after sensor deployment, an algorithm is performed to identify a subset of vehicles that provide the necessary field of view of the target surface.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Muehl with Pescaru’s technique of identifying a subset of the plurality of vehicles corresponding to the identified subset of captured images. It would have been obvious to modify because doing so enables sensor coverage networks to increase energy efficiency while preserving field coverage, as recognized by Pescaru (see at least pg. 6, Section VI).
Regarding Claim 2, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 1 as discussed above, and Muehl additionally teaches further comprising determining that a first vehicle in the subset of vehicles has insufficient charge to support sentinel mode operation, removing respective captured images captured by the first vehicle from the set of available captured images, and generating a revised set of available captured images. See at least [0029], wherein a determination is made as to whether any of the vehicles have sufficient power to support the vehicles’ actions. The actions can include activating particular sensors of the vehicles. Additionally, see at least [0079], wherein the sensor data from vehicles in a deactivated mode is ignored or blocked from the set of available sensor data.
Regarding Claim 3, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 2 as discussed above, and Muehl remains silent on further comprising identifying a first subset of images of the revised set of available captured images that together provide the selected field of view of the parking area. 
Schreiber teaches further comprising identifying a first subset of images of the revised set of available captured images that together provide the selected field of view of the parking area. See at least [0089]-[0095], figure 3, step M3, and figures 11-16, wherein a coverage ratio is calculated, representing the subset of individual sensing coverages 8 (set of available captured images) that together provide a selected field of view of the parking area. In combination with Muehl’s teaching, discussed above, of generated a revised set of available sensor data, this limitation is taught in its entirety.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of identifying a subset of the set of available captured images that together provide a selected field of view of the parking area. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Regarding Claim 4, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 1 as discussed above, and Muehl remains silent on further comprising identifying respective image sensors in each respective vehicle of the subset of vehicles corresponding to the identified subset of captured images.
Schreiber teaches identifying respective image sensors in each respective vehicle of the subset of vehicles corresponding to the identified subset of captured images. See at least [0048], [0068]-[0069], [0075] and figures 2 and 11-16, wherein the identified subset of captures images comprises individual sensing coverages of each vehicle. The individual sensing coverage of each vehicle takes into account the particular sensor of the individual vehicle and its location on the vehicle (front, rear, sides, etc.)
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of identifying respective image sensors in each respective vehicle of the subset of vehicles corresponding to the identified subset of captured images. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Regarding Claim 5, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 4 as discussed above, and Muehl additionally teaches wherein transmitting the message includes transmitting the message to each respective vehicle of the subset of vehicles to activate the respective image sensors. See at least [0062]-[0064] and figure 11, wherein a transmission is initiated to activate a guard mode to each of the vehicles in a subset of vehicles (first and second vehicle). Activating guard mode comprises recording sensor data by the sensors of each vehicle and transmitting the sensor data. Additionally, see at least [0029] and [0041], wherein activation of a vehicle action includes instructing the vehicle to activate a particular sensor of the vehicle.
Regarding Claim 6, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 1 as discussed above, and Muehl remains silent on further comprising determining the selected field of view, including identifying high priority portions of the parking area and low priority portions of the parking area, wherein high priority areas include highly trafficked areas.
Schreiber teaches further comprising determining the selected field of view, including identifying high priority portions of the parking area and low priority portions of the parking area, wherein high priority areas include highly trafficked areas. See at least [0066]-[0067], [0086], and figure 9, wherein the selected field of view of the parking area is divided into subareas of different relevance levels based on the importance of the subarea. The high priority area RA (traffic relevant area) includes roads and areas with higher likelihood of accidents occurring.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of identifying high and low priority portions of the parking area, the high priority areas including highly trafficked areas. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Regarding Claim 7, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 1 as discussed above, and Muehl additionally teaches wherein the selected field of view is a surveillance coverage area of the parking area. See at least [0045] and figure 3, wherein the selected field of view of a parking area.
Muehl remains silent on further comprising determining the surveillance coverage area based on a high definition map and the set of available captured images.
Schreiber teaches further comprising determining the surveillance coverage area based on a high definition map and the set of available captured images. See at least [0084]-[0085] and figure 1, wherein the parking area is obtained based on an acquired high-definition map and shared sensor data.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of determining the surveillance coverage area based on a high definition map and the set of available captured images. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Regarding Claim 8, Muehl teaches system for fleet parking area surveillance. See at least figures 10-15, processor 1010.
comprising: a plurality of vehicles, wherein each of the plurality of vehicles includes a respective sensor suite having a plurality of image sensors. See at least [0045]-[0046] and figure 3, wherein a plurality of vehicles 326 are located in a parking area 322. See at least [0026], [0044] and figure 2, wherein each vehicle includes a sensor suite including sensors 210-216. The sensors can comprise different types of cameras which provide image data. 
wherein each of the plurality of image sensors is configured to capture an image upon vehicle parking in a respective parking space in a parking area. See at least [0002, [0025], [0046], ad figures 3-5, wherein the image sensors of the vehicle provide sensor data when the vehicle is parked in a parking space of a parking area.
the central computer configured to: receive captured images from each of the plurality of image sensors from each respective vehicle of the plurality of vehicles and storing the received captured images as a set of available captured images. See at least [0026], wherein sensor data including image and video data is received from sensors of the vehicle. Additionally, see at least [0054]-[0055] and figures 6-7, wherein the sensor data is stored in a data structure as a set of available sensor data. Additionally, see at least figure 10, processor 1010.
Muehl remains silent on in communication with a dispatch service; a dispatch service in communication with each of the plurality of vehicles and configured to dispatch respective vehicles to the parking area; a central computer in communication with the dispatch service and with each of the plurality of vehicles; process the set of available captured images to identify a respective field of view of the parking area corresponding to each of the set of available captured images; identify a subset of the set of available captured images that together provide a selected field of view of the parking area; identify a subset of the plurality of vehicles corresponding to the identified subset of captured images. As discussed above, Muehl (see figure 3) teaches identifying a subset of vehicles including a first and second vehicle 326 from the plurality of vehicles, but does not specify how the subset is identified.
Schreiber teaches in communication with a dispatch service; a dispatch service in communication with each of the plurality of vehicles and configured to dispatch respective vehicles to the parking area; a central computer in communication with the dispatch service and with each of the plurality of vehicles. See at least [0057]-[0060], [0062], and [0098], wherein vehicles are autonomously dispatched to recommended parking spots by an external cloud computer.
process the set of available captured images to identify a respective field of view of the parking area corresponding to each of the set of available captured images. See at least [0073], [0084]-[0087], [0099], and figure 3, step M2, wherein an individual sensing coverage is identified based on the received parking data from the plurality of vehicles. The individual sensing coverage for a vehicle represents the field of view of the associated sensor of that particular vehicle.
identify a subset of the set of available captured images that together provide a selected field of view of the parking area. See at least [0089]-[0095], figure 3, step M3, and figures 11-16, wherein a coverage ratio is calculated, representing the subset of individual sensing coverages 8 (set of available captured images) that together provide a selected field of view of the parking area.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of dispatching vehicles by a central computer, identifying a respective field of view of the parking area from the set of available captured images, and identifying a subset of the set of available captured images that together provide a selected field of view of the parking area. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Pescaru teaches identify a subset of the plurality of vehicles corresponding to the identified subset of captured images. See at least pg. 3, left column, and figure 1, wherein a set of captured image data is processed to identify and deploy a plurality of sensors that together provide a selected field of view of a target surface. See at least pg. 3, right column and page 5, left column, wherein, after sensor deployment, an algorithm is performed to identify a subset of vehicles that provide the necessary field of view of the target surface.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Muehl with Pescaru’s technique of identifying a subset of the plurality of vehicles corresponding to the identified subset of captured images. It would have been obvious to modify because doing so enables sensor coverage networks to increase energy efficiency while preserving field coverage, as recognized by Pescaru (see at least pg. 6, Section VI).
Regarding Claim 9, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 8 as discussed above, and Muehl additionally teaches wherein the central computer is further configured to determine that each vehicle in the subset of vehicles has sufficient charge to support sentinel mode operation. See at least [0029], wherein a determination is made that each of the vehicles have sufficient power to support the vehicles’ actions. The actions can include activating particular sensors of the vehicles.
Regarding Claim 10, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 9 as discussed above, and Muehl additionally teaches wherein the central computer is further configured to transmit a message to each vehicle in the subset of vehicles to activate the respective sensor suites and enter sentinel mode operation. See at least [0062]-[0064] and figure 11, wherein a transmission is initiated to activate a guard mode to each of the vehicles in a subset of vehicles (first and second vehicle). Activating guard mode comprises recording sensor data by the sensors of each vehicle and transmitting the sensor data.
Regarding Claim 11, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 9 as discussed above, and Muehl additionally teaches wherein the central computer is further configured to: determine that a first vehicle in the subset of vehicles has insufficient charge to support sentinel mode operation, remove respective captured images captured by the first vehicle image sensors from the set of available captured images, and generate a revised set of available captured images. See at least [0029], wherein a determination is made as to whether any of the vehicles have sufficient power to support the vehicles’ actions. The actions can include activating particular sensors of the vehicles. Additionally, see at least [0079], wherein the sensor data from vehicles in a deactivated mode is ignored or blocked from the set of available sensor data.
Regarding Claim 12, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 11 as discussed above, and Muehl remains silent on wherein the subset of the set of available captured images is a first subset of images, and wherein the central computer is further configured to identify a second subset of images from the revised set of available captured images that together provide the selected field of view of the parking area.
Schreiber teaches wherein the subset of the set of available captured images is a first subset of images, and wherein the central computer is further configured to identify a second subset of images from the revised set of available captured images that together provide the selected field of view of the parking area. See at least [0089]-[0095], figure 3, step M3, and figures 11-16, wherein a coverage ratio is calculated, representing the subset of individual sensing coverages 8 (set of available captured images) that together provide a selected field of view of the parking area. In combination with Muehl’s teaching, discussed above, of generated a revised, second set of available sensor data, this limitation is taught in its entirety.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of identifying a subset of the set of available captured images that together provide a selected field of view of the parking area. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Regarding Claim 13, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 8 as discussed above, and Muehl remains silent on wherein the central computer is further configured to: identify respective image sensors corresponding to the identified subset of captured images.
Schreiber teaches wherein the central computer is further configured to: identify respective image sensors corresponding to the identified subset of captured images. See at least [0048], [0068]-[0069], [0075] and figures 2 and 11-16, wherein the identified subset of captures images comprises individual sensing coverages of each vehicle. The individual sensing coverage of each vehicle takes into account the particular sensor of the individual vehicle and its location on the vehicle (front, rear, sides, etc.)
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of identifying respective image sensors in each respective vehicle of the subset of vehicles corresponding to the identified subset of captured images. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Regarding Claim 14, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 13 as discussed above, and Muehl additionally teaches wherein the central computer is further configured to transmit a message to each vehicle in the subset of vehicles to activate the respective identified image sensors. See at least [0062]-[0064] and figure 11, wherein a transmission is initiated to activate a guard mode to each of the vehicles in a subset of vehicles (first and second vehicle). Activating guard mode comprises recording sensor data by the sensors of each vehicle and transmitting the sensor data. Additionally, see at least [0029] and [0041], wherein activation of a vehicle action includes instructing the vehicle to activate a particular sensor of the vehicle.
Regarding Claim 15, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 8 as discussed above, and Muehl remains silent on wherein the central computer is further configured to: identify respective image sensors corresponding to the identified subset of captured images.
Schreiber teaches wherein the central computer is further configured to: identify respective image sensors corresponding to the identified subset of captured images. See at least [0048], [0068]-[0069], [0075] and figures 2 and 11-16, wherein the identified subset of captures images comprises individual sensing coverages of each vehicle. The individual sensing coverage of each vehicle takes into account the particular sensor of the individual vehicle and its location on the vehicle (front, rear, sides, etc.)
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of identifying respective image sensors in each respective vehicle of the subset of vehicles corresponding to the identified subset of captured images. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Regarding Claim 16, Muehl teaches a method for vehicle fleet surveillance comprising: receiving vehicle data from each of a plurality of fleet vehicles parked in respective parking spaces of the plurality of parking spaces, each fleet vehicle having a set of sensors. See at least [0045]-[0046] and figure 3, wherein a plurality of vehicles 326 are located in a parking area 322. Additionally, see at least [0002] and [0046], wherein multiple vehicles are under control/ownership of a fleet operator. See at least [0045]-[0046] and figure 3, wherein a plurality of vehicles 326 are located in a parking area 322. See at least [0026], [0044] and figure 2, wherein each vehicle includes a sensor suite including sensors 210-216. The sensors can comprise different types of cameras which provide image data. See at least [0026], wherein sensor data including image and video data is received from sensors of the vehicle. Additionally, see at least [0054]-[0055] and figures 6-7, wherein the sensor data is stored in a data structure as a set of available sensor data.
Muehl remains silent on receiving a high definition map of a parking area including a plurality of parking spaces; each respective sensor having a respective sensor field of view; determining a surveillance coverage area of the parking area based on the high definition map and the vehicle data; identifying an overlap in the respective sensor fields of view of a subset of the sets of sensors; and selectively deactivating at least one sensor from the set of sensors based on the overlap.
Schreiber teaches receiving a high definition map of a parking area including a plurality of parking spaces; determining a surveillance coverage area based on a high definition map and the vehicle data. See at least [0084]-[0085] and figure 1, wherein the parking area is obtained based on an acquired high-definition map and shared sensor data.
each respective sensor having a respective sensor field of view. See at least [0073], [0084]-[0087], [0099], and figure 3, step M2, wherein an individual sensing coverage is identified based on the received parking data from the plurality of vehicles. The individual sensing coverage for a vehicle represents the field of view of the associated sensor of that particular vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of each respective sensor having an individual sensing coverage, determining the surveillance coverage area based on a high definition map and the set of available captured images. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Pescaru teaches identifying an overlap in the respective sensor fields of view of a subset of the sets of sensors; and selectively deactivating at least one sensor from the set of sensors based on the overlap. See at least pg. 3-4, Section IV, and figure 3, wherein overlapping areas are identified between subsets of sensors in the sensor network. Based on the identified overlapping areas, select sensors are turned off. 
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Muehl with Pescaru’s technique of identifying overlapping areas in the fields of view of a subset of the sets of sensors, and deactivating sensors based on the overlap. It would have been obvious to modify because doing so enables sensor coverage networks to increase energy efficiency while preserving field coverage, as recognized by Pescaru (see at least pg. 6, Section VI).
Regarding Claim 17, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 16 as discussed above, and Muehl additionally teaches wherein the vehicle data includes a plurality of captured images from the respective sets of sensors for each respective fleet vehicle. See at least [0026], wherein sensor data including image and video data is received from sensors of the vehicle. Additionally, see at least [0054]-[0055] and figures 6-7, wherein the sensor data is stored in a data structure as a set of available sensor data.
Regarding Claim 18, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 17 as discussed above, and Muehl remains silent on wherein each fleet vehicle of the plurality of fleet vehicles has a vehicle field of view and further comprising identifying an overlap in respective vehicle fields of view.
Schreiber teaches wherein each fleet vehicle of the plurality of fleet vehicles has a vehicle field of view. See at least [0073], [0084]-[0087], [0099], and figure 3, step M2, wherein an individual sensing coverage is identified based on the received parking data from the plurality of vehicles. The individual sensing coverage for a vehicle represents the field of view of the associated sensors of that particular vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of each respective sensor having an individual sensing coverage, determining the surveillance coverage area based on a high definition map and the set of available captured images. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Pescaru teaches and further comprising identifying an overlap in respective vehicle fields of view. See at least pg. 3-4, Section IV, and figure 3, wherein overlapping areas are identified between subsets of sensors in the sensor network. Based on the identified overlapping areas, select sensors are turned off. In combination with Muehl and Schreiber’s teaching, discussed above, of fleet vehicles with respective fields of view, this limitation is taught in its entirety.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Muehl with Pescaru’s technique of identifying overlapping areas in the fields of view of a subset of the sets of sensors, and deactivating sensors based on the overlap. It would have been obvious to modify because doing so enables sensor coverage networks to increase energy efficiency while preserving field coverage, as recognized by Pescaru (see at least pg. 6, Section VI).
Regarding Claim 19, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 18 as discussed above, and Muehl additionally teaches further comprising determining a respective state of charge for each fleet vehicle of the plurality of fleet vehicles. See at least [0029], wherein a determination is made that each of the vehicles have sufficient power to support the vehicles’ actions. The actions can include activating particular sensors of the vehicles.
Regarding Claim 20, Muehl, Schreiber, and Pescaru in combination teach all of the limitations of Claim 19 as discussed above, and Muehl additionally teaches identifying a first vehicle with a low state of charge. See at least [0029], wherein a determination is made that each of the vehicles have sufficient power to support the vehicles’ actions. The actions can include activating particular sensors of the vehicles.
Muehl remains silent on further comprising identifying a first parking space of the plurality of parking spaces for which a respective first vehicle field of view overlaps with other respective vehicle fields of view, parking the first vehicle in the first parking space, and deactivating the respective set of sensor for the first vehicle.
Schreiber teaches further comprising identifying a first parking space of the plurality of parking spaces, parking the first vehicle in the first parking space. See at least [0057]-[0060], wherein vehicles are autonomously dispatched to recommended parking spots by an external cloud computer. Additionally, see at least [0096], wherein the recommended parking spot for a vehicle calculated based on the sensor coverage ratio of the parking area.  
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify Muehl with Schreiber’s technique of identifying a parking space and parking the vehicle in the parking space. It would have been obvious to modify because doing so enables optimal sensing coverage of a parking environment, resulting in increased safety for traffic participants, as recognized by Schreiber (see at least [0007]-[0009]).
Pescaru teaches identifying a respective first vehicle field of view overlaps with other respective vehicle fields of view, deactivating the respective set of sensor for the first vehicle. See at least pg. 3-4, Section IV, and figure 3, wherein overlapping areas are identified between subsets of sensors in the sensor network. Based on the identified overlapping areas, select sensors are turned off. 
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to further modify Muehl with Pescaru’s technique of identifying overlapping areas in the fields of view of a subset of the sets of sensors, and deactivating sensors based on the overlap. It would have been obvious to modify because doing so enables sensor coverage networks to increase energy efficiency while preserving field coverage, as recognized by Pescaru (see at least pg. 6, Section VI).

Conclusion
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/S.M.J./             Examiner, Art Unit 3667         

/FARIS S ALMATRAHI/             Supervisory Patent Examiner, Art Unit 3667


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