DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
2. This office action is in response to application number 18/309,954 filed on 05/01/2023,
and the amendments and arguments filed on 03/11/2026.
Claims 1, 16, and 18 have been amended.
No claims have been added.
No claims have been cancelled.
Claims 1-20 are currently pending and have been examined.
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11 March 2026 has been entered.
Priority
3. Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119
(a)-(d). The certified copy has been filed in parent Application No. EP22382452.5, filed on 05/10/2022.
Information disclosure statement
4. The information disclosure statement (IDS) submitted on 05/01/2023, 11/17/2023, and 05/07/2025 have been received and considered.
Response to Amendment
5. Applicant' s amendments to the Claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed 01/12/2026. Applicants arguments, see page 1-2 filed on 03/11/2026, with respect to the rejection(s) of claim(s) 1-20 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. A new grounds for rejection is made under 35 USC 103 as necessitated by amendment over Matus (US 20200213825 A1) in view of Smith (US 20040189521 A1) further in view of Kommuri (US 20130120166 A1) and further in view of Whelan (US 20200250995 A1).
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.
6. Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over (US 20200213825 A1) to Matus et al. (hereinafter Matus) in view of (US 20040189521 A1) to Smith et al. (hereinafter Smith) further in view of (US 20130120166 A1) to Kommuri et al. (hereinafter Kommuri) and further in view of Whelan (US 20200250995 A1).
Regarding claim 1, Matus discloses A method comprising: receiving, from a vehicle in transit along a route over a time period associated with a portion of the route, sensor data values from a plurality of mobile electronic devices aboard the vehicle; (Matus Paragraph 0009: “method 100 for improving vehicle movement characteristic determination using a plurality of mobile devices associated with a vehicle (e.g., residing within the vehicle) can include: collecting a first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices, here the first movement dataset is associated with a time period S110;”) (Matus Paragraph 0047: “In an example, Block S130 can include comparing a first movement dataset associated with a first mobile device to a second movement dataset associated with a second mobile device (e.g., to determine similarity or difference in PVA across the movement datasets;”) (Matus Paragraph 0047: “ In another specific example, Block S130 can include detecting that one or more mobile devices are following a travel route consistent with roads and/or other vehicles (e.g., GPS position data that indicates that a mobile device is currently traveling substantially along a highway route, etc.).”) generating vehicle state variables based at least on the sensor data values; Matus Paragraph 0010: “embodiments of the method 100 and/or system 200 can function to collect and process movement data (and/or supplementary data) from a plurality of mobile devices to improve determination of vehicle movement characteristics associated with vehicle movement (e.g., associated with position, velocity, and/or acceleration of the vehicle; vehicular accident events; driver scores describing driving ability; driver and/or passenger classification; etc.”) (Matus Paragraph 0011: “determining a vehicle movement characteristic (e.g., a PVA characteristic for the vehicle) based on movement datasets from the first and the second mobile devices (e.g., for each movement dataset, mapping the sensor values in the movement datasets to individual PVA characteristics,”) applying statistical processing to the vehicle state variables to generate vehicle trajectory data; (Matus Paragraph 0038: “Block S125 recites: processing at least one of a movement dataset and a supplementary dataset. Block S125 functions to process data collected at least in one of Blocks S110, S115, and S120 into a form suitable for determining device association conditions, vehicle movement characteristics, and/or any other suitable data. Processing datasets (e.g., in Block S125 and/or any other suitable portion of the method 100) can include any one or more of: extracting features (e.g., from a plurality of datasets collected at a plurality of mobile devices, etc.), performing pattern recognition on data (e.g., comparing current movement datasets to reference movement datasets), fusing data from multiple sources, combination of values (e.g., averaging values, etc.), compression, conversion (e.g., digital-to-analog conversion, analog-to-digital conversion), performing statistical estimation on data”)
Matus does not disclose […] receiving surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Smith does teach […] receiving surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; (Smith Paragraph 0017: “The FAA has endorsed the Aircraft Communications Addressing and Reporting System (ACARS) system, which uses various data link technologies including the VHF communication band, HF and SATCOM along with a ground station network to allow aircraft to transmit and receive messages of coded data.”) (Smith Paragraph 0072: “The resultant correlated data, as illustrated in FIG. 2, contains a host of information specifically identifying an aircraft. Such information, when correlated with multilateration data, may provide a complete and accurate picture of aircraft identity and position. Such information may be useful to an airline in tracking individual aircraft for business planning purposes.”) (Smith Paragraph 0075: “ Also at the central workstation 304, ACARS data may be received and modulated, providing a roster or look-up table between registration number and aircraft assigned flight number. Thus, the entire system provides an independent air traffic control picture complete with aircraft position and identification by flight number, using only passive radio reception techniques.”) (Smith Paragraph 0084: “ACARS data may be used to determine aircraft weight and identification. Using this information, along with flight track, aircraft thrust may be calculated accurately.”) (Smith Paragraph 0087: “For the purposes of this application, the term "track" is defined as a collection of records or data points which when connected together, represent the two or three dimensional flight path of an airplane, ground vehicle, or the like. A record may comprise a collection of track data. Each track record may carry some measures and a limited history of past positions generally associated with one airplane or ground vehicle.”)
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Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus to include […] receiving surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; taught by Smith. This would have been for the benefit to provide a multilaterion system which can more accurately track aircraft other vehicles eliminating inaccuracies. [Smith Paragraph 0030]
Smith does not teach […] generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Kommuri does teach […] generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; (Kommuri Paragraph 0015: “In this regard, the flight tracking station 104 generally represents a computer or other computing system at the ground operations center 102 that may be operated by ground personnel to monitor and track the flight of the aircraft 120.”) (Kommuri Paragraph 0016: “The communications system 110 generally represents the combination of hardware, software, firmware and/or other components configured to support communications between the flight tracking station 104 and the aircraft 120”) (Kommuri Paragraph 0017: “The aviation monitoring system 118 may be realized as SIGMET reporting system (or data feed), NOTAM reporting system (or data feed), PIREP reporting system (or data feed), an aircraft report (AIREP) reporting system (or data feed), an airmen's meteorological information (AIRMET) reporting system (or data feed), a METAR monitoring system, an aircraft situation display to industry (ASDI) reporting system (or data feed), a central flow management unit (CMFU), an automatic dependent surveillance-broadcast (ADS-B) system, an airport delay reporting system (or data feed),”) (Kommuri Paragraph 0019: “As described in greater detail below, in accordance with one exemplary embodiment, the ground personnel at the flight tracking station 104 manipulates the user input device 106 to display the projected flight path corresponding to the originally scheduled flight plan for the aircraft 120 on the flight tracking map, modify one or more navigational reference points of the flight plan on the flight tracking map to create modified flight plan that avoids any regions identified by one of the external monitoring systems 116, 118 that may interfere with operation of the aircraft 120 (e.g., regions of high turbulence, convection, precipitation, air traffic, or the like),”) (Kommuri Paragraph 0024: “The navigation system 132 is capable of obtaining and/or determining the instantaneous position of the aircraft 120, that is, the current (or instantaneous) location of the aircraft 120 (e.g., the current latitude and longitude) and the current (or instantaneous) altitude (or above ground level) for the aircraft 120. The navigation system 132 is also capable of obtaining or otherwise determining the heading of the aircraft 120 (i.e., the direction the aircraft is traveling in relative to some reference).”) (Kommuri Paragraph 0028: “Still referring to FIG. 2, and with continued reference to FIG. 1, in an exemplary embodiment, the flight monitoring process 200 begins by rendering or otherwise displaying a flight tracking display associated with an aircraft being monitored on a display device at a flight tracking station on the ground (task 202). In accordance with one or more embodiments, the processing system 112 obtains the current location of the aircraft 120 (e.g., from the navigation system 132 and/or FMS 134 via communications systems 110, 130), and based on the location of the aircraft 120, the processing system 112 utilizes the information in the data storage element 114 to display a flight tracking map associated with the aircraft 120 on the display device 108.”)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus in view of Smith to include […] generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; taught by Kommuri. This would have been for the benefit to provide an exemplary method involves capturing, by a computing system at a ground location, a flight tracking image associated with the aircraft that is displayed on a first display device at the ground location, and communicating the captured flight tracking image to the aircraft for display on a second display device onboard the aircraft. Thus providing help to the pilot so the pilot of the aircraft can analyze information being relied on by the ground personnel so the pilot has more situational awareness of how to proceed to operate the aircraft. [Kommuri Paragraph 0002 and 0003]
Kommuri does not teach […] and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Whelan does teach […] and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data. (Whelan Paragraph 0064: “FIG. 11 illustrates an example of displaying delay information on a mobile device 1108, in accordance with one or more embodiments of the present disclosure.”) (Whelan Paragraph 0064: “The device 1108 could also provide additional information on how it reached its decision 1110 and or suggest alternative routes (e.g. possible remedies) 1112.”) (Whelan Paragraph 0066:“In some embodiments, AID 1204 provides a secure wireless network. The pilot accesses flight data through this network using their mobile device 1208. In some embodiments, the mobile device 1208 contains software which informs the pilot if a delay is possible with concerns to the current flight or route.”)
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Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus in view of Smith further in view of Kommuri to include […] and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data taught by Whelan. This would have been for the benefit to provide a mobile device, a data acquisition device, a processor, and memory that will be used to improved delay prevention in airline scheduling. [Whelan Paragraph 0003 and 0005]
Regarding claim 2, Matus discloses The method of claim 1, wherein generating the vehicle state variables comprises processing the sensor data values to identify one or more representative sensor data values. (Matus Paragraph 0009: “collecting a first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices, where the first movement dataset is associated with a time period S110;”) (Matus Paragraph 0061: “and determining an overall vehicle movement characteristic (e.g., overall PVA characteristic; average PVA characteristic; weighted PVA characteristic; etc.) based on the first and the second vehicle movement characteristics, such as through processing the individual movement characteristics”)
Regarding claim 3, Matus discloses The method of claim 2, wherein processing the sensor data values to identify one or more representative sensor data values comprises removing one or more outlying data values from the sensor data values. (Matus Paragraph 0042: “In another specific example, the method 100 can include collecting movement datasets from a first, second, and third mobile device; and filtering movement data outliers from movement data collected at the first mobile device based on inconsistency with movement data collected at the second and the third mobile devices.”)
Regarding claim 4, Matus discloses The method of claim 1, wherein first sensor data values received from a first mobile electronic device of the plurality of mobile electronic devices comprise one or more representative sensor data values generated by the first mobile electronic device, the one or more representative sensor data values associated with a plurality of sensor values generated by sensors of the first mobile electronic device during the time period. (Matus Paragraph 0021: “collecting a first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices, where the first movement dataset is associated with a time period S110.”) (Matus Paragraph 0038: “different data collected at different mobile devices, different data types, same data type, etc.) based on a common and/or overlapping temporal indicator (e.g., time point, time window, time period, etc.), which can enable data collected from multiple sources during a common temporal indicator to be processed and/or analyzed together.”)
Regarding claim 5, Matus discloses The method of claim 4, wherein at least one of the one or more representative sensor data values comprises an average of the plurality of sensor values, a range of the sensor values, one or more bins of the plurality of sensor values, a variance associated with the plurality of sensor values, or an omission of one or more outlying data values of the plurality of sensor data values. (Matus Paragraph 0009: “collecting a first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices, where the first movement dataset is associated with a time period S110; collecting a second movement dataset corresponding to at least one of a second location sensor and a second motion sensor of a second mobile device of the plurality of mobile devices, where the second movement dataset is associated with the time period S115;”) (Matus Paragraph 0042: “In another specific example, the method 100 can include collecting movement datasets from a first, second, and third mobile device; and filtering movement data outliers from movement data collected at the first mobile device based on inconsistency with movement data collected at the second and the third mobile devices.”)
Regarding claim 6, Matus in view of Smith and further in view of Kommuri teaches claim 1, accordingly, the rejection of claim 1 is incorporated above.
Matus does not teach The method of claim 1, wherein the surveillance data includes radar tracking data.
However, Smith does teach The method of claim 1, wherein the surveillance data includes radar tracking data. (Smith Paragraph 0073: “the integration of ACARS and SSR data is shown with an aircraft multilateration system. Aircraft 300 transmits SSR signals 301 at least once per second. SSR signals 301 may be received at one or more of multiple ground stations 302.”)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus to include The method of claim 1, wherein the surveillance data includes radar tracking data taught by Smith. This would have been for the benefit to provide a multilaterion system which can more accurately track aircraft other vehicles eliminating inaccuracies. [Smith Paragraph 0030]
Regarding claim 7, Matus discloses The method of claim 1, wherein the statistical processing comprises removing one or more outlying data values from the vehicle state variables. (Matus Paragraph 0038: “Block S125 recites: processing at least one of a movement dataset and a supplementary dataset. Block S125 functions to process data collected at least in one of Blocks S110, S115, and S120 into a form suitable for determining device association conditions, vehicle movement characteristics, and/or any other suitable data. Processing datasets (e.g., in Block S125 and/or any other suitable portion of the method 100) can include any one or more of: extracting features (e.g., from a plurality of datasets collected at a plurality of mobile devices, etc.), performing pattern recognition on data (e.g., comparing current movement datasets to reference movement datasets), fusing data from multiple sources, combination of values (e.g., averaging values, etc.), compression, conversion (e.g., digital-to-analog conversion, analog-to-digital conversion), performing statistical estimation on data (e.g. ordinary least squares regression, non-negative least squares regression, principal components analysis, ridge regression, etc.)”) (Matus Paragraph 0042: “In another specific example, the method 100 can include collecting movement datasets from a first, second, and third mobile device; and filtering movement data outliers from movement data collected at the first mobile device”)
Regarding claim 8, Matus discloses The method of claim 1, wherein the statistical processing comprises applying one or more Kalman filters to the vehicle state variables. (Matus Paragraph 0038: “Block S125 recites: processing at least one of a movement dataset and a supplementary dataset. Block S125 functions to process data collected at least in one of Blocks S110, S115, and S120 into a form suitable for determining device association conditions, vehicle movement characteristics, and/or any other suitable data. Processing datasets (e.g., in Block S125 and/or any other suitable portion of the method 100) can include any one or more of: extracting features (e.g., from a plurality of datasets collected at a plurality of mobile devices, etc.), performing pattern recognition on data (e.g., comparing current movement datasets to reference movement datasets), fusing data from multiple sources, combination of values (e.g., averaging values, etc.), compression, conversion (e.g., digital-to-analog conversion, analog-to-digital conversion), performing statistical estimation on data (e.g. ordinary least squares regression, non-negative least squares regression, principal components analysis, ridge regression, etc.)”)
Regarding claim 9, Matus discloses The method of claim 1, wherein at least one of the sensor data values originates from a global positioning system (“GPS”) component of one of the mobile electronic devices, an inertial measurement unit (“IMU”) component of one of the mobile electronic devices, a barometer of one of the mobile electronic devices, or a biometric sensor of one of the mobile electronic devices. (Matus Paragraph 0021: “first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices”) (Matus Paragraph 0022: “Movement datasets are preferably sampled at one or more movement sensors indicative of one or more of motion and/or location, which can include one or more of: motion sensors (e.g., multi-axis and/or single-axis accelerometers, gyroscopes, etc.), location sensors (e.g., GPS data collection components, magnetometer, compass, altimeter, etc.), optical sensors, audio sensors, electromagnetic (EM)-related sensors (e.g., radar, lidar, sonar, ultrasound, infrared radiation, magnetic positioning, etc.), environmental sensors (e.g., temperature sensors, altitude sensors, pressure sensors, etc.), biometric sensors”).
Regarding claim 10, Matus discloses The method of claim 1, further comprising communicating the vehicle trajectory data to a vehicle operations center. (Matus Paragraph 0019: The technology can amount to an inventive distribution of functionality across a network including a plurality of mobile devices associated with a moving vehicle, and a vehicle movement determination system (e.g., a remote computing system, etc.) (Note: Vehicle operations center can be can be a physical and/or logical collection of electronic components) (Matus Paragraph 0023: Inn another variation, Block S110 can include collecting movement data from data collected at the vehicle (e.g., vehicle sensors described herein and/or other suitable vehicle sensors), where the movement data can be received through wired communication (e.g., transmission of data from the vehicle to a mobile device through a wired communication channel, etc.) and/or wireless communication (e.g., transmission of data from the vehicle to a remote vehicle movement determination system through WiFi;) (Matus Paragraph 0039: “Movement features are preferably associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during a time period.”)
Regarding claim 11, Matus discloses The method of claim 1, further comprising: receiving, from a second vehicle in transit along a second route over a second time period associated with a portion of the second route, second sensor data values from a second plurality of mobile electronic devices aboard the second vehicle; (Matus Paragraph 0046: “e.g., and a movement dataset associated with the second mobile device, such as the second subsequent movement dataset; where the second device association condition can be indicative of the second user entering a second vehicle”) (Matus Paragraph 0047: “In another specific example, Block S130 can include detecting that one or more mobile devices are following a travel route consistent with roads and/or other vehicles”) (Note: It is Possible for different routes to be determined and followed) (Matus Paragraph 0060: “In another variation, Block S140 can be based on data collected by different devices at different time periods”) (Matus Paragraph 0060: “collecting a second movement dataset during a second potion of the time period (e.g., a second half of the time period, etc.);”) generating second vehicle state variables based at least on the second sensor data values; (Matus Paragraph 0009: “determining a vehicle movement characteristic based on the first and the second movement datasets, where the vehicle movement characteristic describes movement of the vehicle S140”) (Matus Paragraph 0010: “embodiments of the method 100 and/or system 200 can function to collect and process movement data (and/or supplementary data) from a plurality of mobile devices to improve determination of vehicle movement characteristics associated with vehicle movement (e.g., associated with position, velocity, and/or acceleration of the vehicle; vehicular accident events; driver scores describing driving ability; driver and/or passenger classification; etc.”) (Matus Paragraph 0011: “determining a vehicle movement characteristic (e.g., a PVA characteristic for the vehicle) based on movement datasets from the first and the second mobile devices (e.g., for each movement dataset, mapping the sensor values in the movement datasets to individual PVA characteristics,”) and applying statistical processing to the second vehicle state variables to generate second vehicle trajectory data. (Matus Paragraph 0038: “Block S125 recites: processing at least one of a movement dataset and a supplementary dataset. Block S125 functions to process data collected at least in one of Blocks S110, S115, and S120 into a form suitable for determining device association conditions, vehicle movement characteristics, and/or any other suitable data. Processing datasets (e.g., in Block S125 and/or any other suitable portion of the method 100) can include any one or more of: extracting features (e.g., from a plurality of datasets collected at a plurality of mobile devices, etc.), performing pattern recognition on data (e.g., comparing current movement datasets to reference movement datasets), fusing data from multiple sources, combination of values (e.g., averaging values, etc.), compression, conversion (e.g., digital-to-analog conversion, analog-to-digital conversion), performing statistical estimation on data”)
Regarding claim 12, Matus discloses The method of claim 1, wherein the sensor data values are received via a wireless link between the vehicle and a vehicle operations center. (Matus Paragraph 0019: The technology can amount to an inventive distribution of functionality across a network including a plurality of mobile devices associated with a moving vehicle, and a vehicle movement determination system (e.g., a remote computing system, etc.) (Note: Vehicle operations center can be can be a physical and/or logical collection of electronic components) (Matus Paragraph 0023: Inn another variation, Block S110 can include collecting movement data from data collected at the vehicle (e.g., vehicle sensors described herein and/or other suitable vehicle sensors), where the movement data can be received through wired communication (e.g., transmission of data from the vehicle to a mobile device through a wired communication channel, etc.) and/or wireless communication (e.g., transmission of data from the vehicle to a remote vehicle movement determination system through WiFi;) (Matus Paragraph 0039: “Movement features are preferably associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during a time period.”)
Regarding claim 13, Matus discloses The method of claim 1, wherein the vehicle includes an aircraft and the plurality of mobile electronic devices include smartphones onboard the aircraft. (Matus Paragraph 0012: “The method 100 is preferably implemented using a plurality of mobile devices (e.g., smartphones, laptops, tablets, smart watches, smart glasses, virtual reality devices, augmented reality devices, aerial devices such as drones, medical devices, etc.) removably coupled to one or more vehicles (e.g., motor vehicles, bicycles, watercraft, aircraft, spacecraft, railed vehicles, autonomous vehicles, etc.”).
Regarding claim 14, Matus discloses The method of claim 13, wherein each of the smartphones includes a vehicle data collection application to cause sensors of at least one of the smartphones to collect the sensor data values (Matus Paragraph 0012: “The method 100 is preferably implemented using a plurality of mobile devices (e.g., smartphones,”) (Matus Paragraph 0023: “Block S110 can include deriving movement data from visual data (e.g., deriving PVA data from video taken by a smartphone's camera and/or vehicle camera; derived from visual markers captured in optical data, such as geographical markers, markers indicated by satellite imagery; etc.) and/or audio data (e.g., deriving motion from Doppler effects captured in data from the smartphone's microphone, etc.).”) and communicate the sensor data values to a wireless internet router onboard the aircraft. (Matus Paragraph 0050: “In a specific example, the method 100 can include detecting a first wireless signal between a first mobile device and a wireless communication system (e.g., a WiFi hot spot associated with the vehicle;”) (Note: Hotspot is an internet wireless router)
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Regarding claim 15, Matus discloses The method of claim 14, wherein the wireless internet router causes the sensor data values to be communicated to a vehicle operations center. (Matus Paragraph 0019: “a vehicle movement determination system (e.g., a remote computing system, etc.)”) (Note: Vehicle operations center can be can be a physical and/or logical collection of electronic components) (Matus Paragraph 0023: “and/or wireless communication (e.g., transmission of data from the vehicle to a remote vehicle movement determination system through WiFi;”) (Note: The data is transmitted based on wireless communication which could be a WiFi Hotspot) (Matus Paragraph 0050: “In a specific example, the method 100 can include detecting a first wireless signal between a first mobile device and a wireless communication system (e.g., a WiFi hot spot associated with the vehicle;”) (Note: Hotspot is an internet wireless router)
Regarding claim 16, Matus discloses A non-transient, computer-readable medium storing instructions executable by one or more processors to perform operations that include: (Matus Paragraph 0067: “The system and method and embodiments thereof can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions.”) receiving, from a vehicle in transit over a time period associated with a portion of the transit, sensor data values from a plurality of mobile electronic devices aboard the vehicle; (Matus Paragraph 0009: “method 100 for improving vehicle movement characteristic determination using a plurality of mobile devices associated with a vehicle (e.g., residing within the vehicle) can include: collecting a first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices, here the first movement dataset is associated with a time period S110;”) (Matus Paragraph 0047: “In an example, Block S130 can include comparing a first movement dataset associated with a first mobile device to a second movement dataset associated with a second mobile device (e.g., to determine similarity or difference in PVA across the movement datasets;”) (Matus Paragraph 0047: “ In another specific example, Block S130 can include detecting that one or more mobile devices are following a travel route consistent with roads and/or other vehicles (e.g., GPS position data that indicates that a mobile device is currently traveling substantially along a highway route, etc.).”) generating vehicle state variables based at least on the sensor data values; (Matus Paragraph 0010: “embodiments of the method 100 and/or system 200 can function to collect and process movement data (and/or supplementary data) from a plurality of mobile devices to improve determination of vehicle movement characteristics associated with vehicle movement (e.g., associated with position, velocity, and/or acceleration of the vehicle; vehicular accident events; driver scores describing driving ability; driver and/or passenger classification; etc.”) (Matus Paragraph 0011: “determining a vehicle movement characteristic (e.g., a PVA characteristic for the vehicle) based on movement datasets from the first and the second mobile devices (e.g., for each movement dataset, mapping the sensor values in the movement datasets to individual PVA characteristics,”) applying statistical processing to the vehicle state variables to generate vehicle trajectory data; (Matus Paragraph 0038: “Block S125 recites: processing at least one of a movement dataset and a supplementary dataset. Block S125 functions to process data collected at least in one of Blocks S110, S115, and S120 into a form suitable for determining device association conditions, vehicle movement characteristics, and/or any other suitable data. Processing datasets (e.g., in Block S125 and/or any other suitable portion of the method 100) can include any one or more of: extracting features (e.g., from a plurality of datasets collected at a plurality of mobile devices, etc.), performing pattern recognition on data (e.g., comparing current movement datasets to reference movement datasets), fusing data from multiple sources, combination of values (e.g., averaging values, etc.), compression, conversion (e.g., digital-to-analog conversion, analog-to-digital conversion), performing statistical estimation on data”)
Matus does not disclose […] receiving surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Smith does teach […] receiving surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; (Smith Paragraph 0017: “The FAA has endorsed the Aircraft Communications Addressing and Reporting System (ACARS) system, which uses various data link technologies including the VHF communication band, HF and SATCOM along with a ground station network to allow aircraft to transmit and receive messages of coded data.”) (Smith Paragraph 0072: “The resultant correlated data, as illustrated in FIG. 2, contains a host of information specifically identifying an aircraft. Such information, when correlated with multilateration data, may provide a complete and accurate picture of aircraft identity and position. Such information may be useful to an airline in tracking individual aircraft for business planning purposes.”) (Smith Paragraph 0075: “ Also at the central workstation 304, ACARS data may be received and modulated, providing a roster or look-up table between registration number and aircraft assigned flight number. Thus, the entire system provides an independent air traffic control picture complete with aircraft position and identification by flight number, using only passive radio reception techniques.”) (Smith Paragraph 0084: “ACARS data may be used to determine aircraft weight and identification. Using this information, along with flight track, aircraft thrust may be calculated accurately.”) (Smith Paragraph 0087: “For the purposes of this application, the term "track" is defined as a collection of records or data points which when connected together, represent the two or three dimensional flight path of an airplane, ground vehicle, or the like. A record may comprise a collection of track data. Each track record may carry some measures and a limited history of past positions generally associated with one airplane or ground vehicle.”)
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Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus to include […] receiving surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; taught by Smith. This would have been for the benefit to provide a multilaterion system which can more accurately track aircraft other vehicles eliminating inaccuracies. [Smith Paragraph 0030]
Smith does not teach […] generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Kommuri does teach […] generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; (Kommuri Paragraph 0015: “In this regard, the flight tracking station 104 generally represents a computer or other computing system at the ground operations center 102 that may be operated by ground personnel to monitor and track the flight of the aircraft 120.”) (Kommuri Paragraph 0016: “The communications system 110 generally represents the combination of hardware, software, firmware and/or other components configured to support communications between the flight tracking station 104 and the aircraft 120”) (Kommuri Paragraph 0017: “The aviation monitoring system 118 may be realized as SIGMET reporting system (or data feed), NOTAM reporting system (or data feed), PIREP reporting system (or data feed), an aircraft report (AIREP) reporting system (or data feed), an airmen's meteorological information (AIRMET) reporting system (or data feed), a METAR monitoring system, an aircraft situation display to industry (ASDI) reporting system (or data feed), a central flow management unit (CMFU), an automatic dependent surveillance-broadcast (ADS-B) system, an airport delay reporting system (or data feed),”) (Kommuri Paragraph 0019: “As described in greater detail below, in accordance with one exemplary embodiment, the ground personnel at the flight tracking station 104 manipulates the user input device 106 to display the projected flight path corresponding to the originally scheduled flight plan for the aircraft 120 on the flight tracking map, modify one or more navigational reference points of the flight plan on the flight tracking map to create modified flight plan that avoids any regions identified by one of the external monitoring systems 116, 118 that may interfere with operation of the aircraft 120 (e.g., regions of high turbulence, convection, precipitation, air traffic, or the like),”) (Kommuri Paragraph 0024: “The navigation system 132 is capable of obtaining and/or determining the instantaneous position of the aircraft 120, that is, the current (or instantaneous) location of the aircraft 120 (e.g., the current latitude and longitude) and the current (or instantaneous) altitude (or above ground level) for the aircraft 120. The navigation system 132 is also capable of obtaining or otherwise determining the heading of the aircraft 120 (i.e., the direction the aircraft is traveling in relative to some reference).”) (Kommuri Paragraph 0028: “Still referring to FIG. 2, and with continued reference to FIG. 1, in an exemplary embodiment, the flight monitoring process 200 begins by rendering or otherwise displaying a flight tracking display associated with an aircraft being monitored on a display device at a flight tracking station on the ground (task 202). In accordance with one or more embodiments, the processing system 112 obtains the current location of the aircraft 120 (e.g., from the navigation system 132 and/or FMS 134 via communications systems 110, 130), and based on the location of the aircraft 120, the processing system 112 utilizes the information in the data storage element 114 to display a flight tracking map associated with the aircraft 120 on the display device 108.”)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus in view of Smith to include […] generating vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; taught by Kommuri. This would have been for the benefit to provide an exemplary method involves capturing, by a computing system at a ground location, a flight tracking image associated with the aircraft that is displayed on a first display device at the ground location, and communicating the captured flight tracking image to the aircraft for display on a second display device onboard the aircraft. Thus providing help to the pilot so the pilot of the aircraft can analyze information being relied on by the ground personnel so the pilot has more situational awareness of how to proceed to operate the aircraft. [Kommuri Paragraph 0002 and 0003]
Kommuri does not teach […] and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Whelan does teach […] and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data. (Whelan Paragraph 0064: “FIG. 11 illustrates an example of displaying delay information on a mobile device 1108, in accordance with one or more embodiments of the present disclosure.”) (Whelan Paragraph 0064: “The device 1108 could also provide additional information on how it reached its decision 1110 and or suggest alternative routes (e.g. possible remedies) 1112.”) (Whelan Paragraph 0066:“In some embodiments, AID 1204 provides a secure wireless network. The pilot accesses flight data through this network using their mobile device 1208. In some embodiments, the mobile device 1208 contains software which informs the pilot if a delay is possible with concerns to the current flight or route.”)
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Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus in view of Smith further in view of Kommuri to include […] and transmitting the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data taught by Whelan. This would have been for the benefit to provide a mobile device, a data acquisition device, a processor, and memory that will be used to improved delay prevention in airline scheduling. [Whelan Paragraph 0003 and 0005]
Regarding claim 17, Matus discloses The non-transient, computer-readable medium of claim 16, wherein: the vehicle includes an aircraft and the plurality of mobile electronic devices include smartphones onboard the aircraft; and each of the smartphones includes a vehicle data collection application to cause sensors of at least one of the smartphones to collect the sensor data values and communicate the sensor data values to a wireless internet router onboard the aircraft. (Matus Paragraph 0012: “The method 100 is preferably implemented using a plurality of mobile devices (e.g., smartphones,”) (Matus Paragraph 0023: “Block S110 can include deriving movement data from visual data (e.g., deriving PVA data from video taken by a smartphone's camera and/or vehicle camera; derived from visual markers captured in optical data, such as geographical markers, markers indicated by satellite imagery; etc.) and/or audio data (e.g., deriving motion from Doppler effects captured in data from the smartphone's microphone, etc.).”) (Matus Paragraph 0050: “In a specific example, the method 100 can include detecting a first wireless signal between a first mobile device and a wireless communication system (e.g., a WiFi hot spot associated with the vehicle;”) (Note: Hotspot is an internet wireless router)
Regarding claim 18, Matus discloses A system comprising: a memory configured to store instructions; and one or more processors configured to: (Matus Paragraph 0067: “The system and method and embodiments thereof can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions.”) receive, from a vehicle in transit, over a time period associated with a portion of the transit, sensor data values from a plurality of mobile electronic devices aboard the vehicle; (Matus Paragraph 0009: “method 100 for improving vehicle movement characteristic determination using a plurality of mobile devices associated with a vehicle (e.g., residing within the vehicle) can include: collecting a first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices, here the first movement dataset is associated with a time period S110;”) (Matus Paragraph 0047: “In an example, Block S130 can include comparing a first movement dataset associated with a first mobile device to a second movement dataset associated with a second mobile device (e.g., to determine similarity or difference in PVA across the movement datasets;”) (Matus Paragraph 0047: “ In another specific example, Block S130 can include detecting that one or more mobile devices are following a travel route consistent with roads and/or other vehicles (e.g., GPS position data that indicates that a mobile device is currently traveling substantially along a highway route, etc.).”) generate vehicle state variables based at least on the sensor data values; (Matus Paragraph 0010: “embodiments of the method 100 and/or system 200 can function to collect and process movement data (and/or supplementary data) from a plurality of mobile devices to improve determination of vehicle movement characteristics associated with vehicle movement (e.g., associated with position, velocity, and/or acceleration of the vehicle; vehicular accident events; driver scores describing driving ability; driver and/or passenger classification; etc.”) (Matus Paragraph 0011: “determining a vehicle movement characteristic (e.g., a PVA characteristic for the vehicle) based on movement datasets from the first and the second mobile devices (e.g., for each movement dataset, mapping the sensor values in the movement datasets to individual PVA characteristics,”) apply statistical processing to the vehicle state variables to generate vehicle trajectory data; (Matus Paragraph 0038: “Block S125 recites: processing at least one of a movement dataset and a supplementary dataset. Block S125 functions to process data collected at least in one of Blocks S110, S115, and S120 into a form suitable for determining device association conditions, vehicle movement characteristics, and/or any other suitable data. Processing datasets (e.g., in Block S125 and/or any other suitable portion of the method 100) can include any one or more of: extracting features (e.g., from a plurality of datasets collected at a plurality of mobile devices, etc.), performing pattern recognition on data (e.g., comparing current movement datasets to reference movement datasets), fusing data from multiple sources, combination of values (e.g., averaging values, etc.), compression, conversion (e.g., digital-to-analog conversion, analog-to-digital conversion), performing statistical estimation on data”)
Matus does not disclose […] receive surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; generate vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; and transmit the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Smith does teach […] receive surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; (Smith Paragraph 0017: “The FAA has endorsed the Aircraft Communications Addressing and Reporting System (ACARS) system, which uses various data link technologies including the VHF communication band, HF and SATCOM along with a ground station network to allow aircraft to transmit and receive messages of coded data.”) (Smith Paragraph 0072: “The resultant correlated data, as illustrated in FIG. 2, contains a host of information specifically identifying an aircraft. Such information, when correlated with multilateration data, may provide a complete and accurate picture of aircraft identity and position. Such information may be useful to an airline in tracking individual aircraft for business planning purposes.”) (Smith Paragraph 0075: “ Also at the central workstation 304, ACARS data may be received and modulated, providing a roster or look-up table between registration number and aircraft assigned flight number. Thus, the entire system provides an independent air traffic control picture complete with aircraft position and identification by flight number, using only passive radio reception techniques.”) (Smith Paragraph 0084: “ACARS data may be used to determine aircraft weight and identification. Using this information, along with flight track, aircraft thrust may be calculated accurately.”) (Smith Paragraph 0087: “For the purposes of this application, the term "track" is defined as a collection of records or data points which when connected together, represent the two or three dimensional flight path of an airplane, ground vehicle, or the like. A record may comprise a collection of track data. Each track record may carry some measures and a limited history of past positions generally associated with one airplane or ground vehicle.”)
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Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus to include […] receive surveillance data associated with external tracking of one or more trajectory aspects of the vehicle in transit by an external tracking surveillance device, wherein the surveillance data is generated independent of the plurality of mobile electronic devices; taught by Smith. This would have been for the benefit to provide a multilaterion system which can more accurately track aircraft other vehicles eliminating inaccuracies. [Smith Paragraph 0030]
Smith does not teach […] generate vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; and transmit the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Kommuri does teach […] generate vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; (Kommuri Paragraph 0015: “In this regard, the flight tracking station 104 generally represents a computer or other computing system at the ground operations center 102 that may be operated by ground personnel to monitor and track the flight of the aircraft 120.”) (Kommuri Paragraph 0016: “The communications system 110 generally represents the combination of hardware, software, firmware and/or other components configured to support communications between the flight tracking station 104 and the aircraft 120”) (Kommuri Paragraph 0017: “The aviation monitoring system 118 may be realized as SIGMET reporting system (or data feed), NOTAM reporting system (or data feed), PIREP reporting system (or data feed), an aircraft report (AIREP) reporting system (or data feed), an airmen's meteorological information (AIRMET) reporting system (or data feed), a METAR monitoring system, an aircraft situation display to industry (ASDI) reporting system (or data feed), a central flow management unit (CMFU), an automatic dependent surveillance-broadcast (ADS-B) system, an airport delay reporting system (or data feed),”) (Kommuri Paragraph 0019: “As described in greater detail below, in accordance with one exemplary embodiment, the ground personnel at the flight tracking station 104 manipulates the user input device 106 to display the projected flight path corresponding to the originally scheduled flight plan for the aircraft 120 on the flight tracking map, modify one or more navigational reference points of the flight plan on the flight tracking map to create modified flight plan that avoids any regions identified by one of the external monitoring systems 116, 118 that may interfere with operation of the aircraft 120 (e.g., regions of high turbulence, convection, precipitation, air traffic, or the like),”) (Kommuri Paragraph 0024: “The navigation system 132 is capable of obtaining and/or determining the instantaneous position of the aircraft 120, that is, the current (or instantaneous) location of the aircraft 120 (e.g., the current latitude and longitude) and the current (or instantaneous) altitude (or above ground level) for the aircraft 120. The navigation system 132 is also capable of obtaining or otherwise determining the heading of the aircraft 120 (i.e., the direction the aircraft is traveling in relative to some reference).”) (Kommuri Paragraph 0028: “Still referring to FIG. 2, and with continued reference to FIG. 1, in an exemplary embodiment, the flight monitoring process 200 begins by rendering or otherwise displaying a flight tracking display associated with an aircraft being monitored on a display device at a flight tracking station on the ground (task 202). In accordance with one or more embodiments, the processing system 112 obtains the current location of the aircraft 120 (e.g., from the navigation system 132 and/or FMS 134 via communications systems 110, 130), and based on the location of the aircraft 120, the processing system 112 utilizes the information in the data storage element 114 to display a flight tracking map associated with the aircraft 120 on the display device 108.”)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus in view of Smith to include […] generate vehicle track data based at least on the vehicle trajectory data and the surveillance data, wherein the vehicle track data includes particular data that indicates whether the vehicle is delayed; taught by Kommuri. This would have been for the benefit to provide an exemplary method involves capturing, by a computing system at a ground location, a flight tracking image associated with the aircraft that is displayed on a first display device at the ground location, and communicating the captured flight tracking image to the aircraft for display on a second display device onboard the aircraft. Thus providing help to the pilot so the pilot of the aircraft can analyze information being relied on by the ground personnel so the pilot has more situational awareness of how to proceed to operate the aircraft. [Kommuri Paragraph 0002 and 0003]
Kommuri does not teach […] and transmit the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data.
However, Whelan does teach […] and transmit the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data. (Whelan Paragraph 0064: “FIG. 11 illustrates an example of displaying delay information on a mobile device 1108, in accordance with one or more embodiments of the present disclosure.”) (Whelan Paragraph 0064: “The device 1108 could also provide additional information on how it reached its decision 1110 and or suggest alternative routes (e.g. possible remedies) 1112.”) (Whelan Paragraph 0066:“In some embodiments, AID 1204 provides a secure wireless network. The pilot accesses flight data through this network using their mobile device 1208. In some embodiments, the mobile device 1208 contains software which informs the pilot if a delay is possible with concerns to the current flight or route.”)
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Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Matus in view of Smith further in view of Kommuri to include […] and transmit the vehicle track data to the plurality of mobile electronic devices, wherein transmitting the vehicle track data causes at least one mobile electronic device of the plurality of mobile electronic devices to display a portion of the vehicle track data including the particular data taught by Whelan. This would have been for the benefit to provide a mobile device, a data acquisition device, a processor, and memory that will be used to improved delay prevention in airline scheduling. [Whelan Paragraph 0003 and 0005]
Regarding claim 19, Matus discloses The system of claim 18, wherein: the vehicle includes an aircraft and the plurality of mobile electronic devices include smartphones onboard the aircraft; and each of the smartphones includes a vehicle data collection application to cause sensors of at least one of the smartphones to collect the sensor data values and communicate the sensor data values to a wireless internet router onboard the aircraft. (Matus Paragraph 0012: “The method 100 is preferably implemented using a plurality of mobile devices (e.g., smartphones,”) (Matus Paragraph 0023: “Block S110 can include deriving movement data from visual data (e.g., deriving PVA data from video taken by a smartphone's camera and/or vehicle camera; derived from visual markers captured in optical data, such as geographical markers, markers indicated by satellite imagery; etc.) and/or audio data (e.g., deriving motion from Doppler effects captured in data from the smartphone's microphone, etc.).”) (Matus Paragraph 0050: “In a specific example, the method 100 can include detecting a first wireless signal between a first mobile device and a wireless communication system (e.g., a WiFi hot spot associated with the vehicle;”) (Note: Hotspot is an internet wireless router)
Regarding claim 20, Matus discloses The system of claim 18, wherein at least one of the sensor data values originates from a global positioning system ("GPS") component of one of the mobile electronic devices, an inertial measurement unit ("IMU") component of one of the mobile electronic devices, a barometer of one of the mobile electronic devices, or a biometric sensor of one of the mobile electronic devices. (Matus Paragraph 0021: “first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices”) (Matus Paragraph 0022: “Movement datasets preferably describe at least one of position, velocity, and/or acceleration (PVA) of one or more vehicles, user devices (e.g., user smartphones), users, and/or any other suitable entities, but can additionally or alternatively describe any suitable movement-related characteristic.”) (Matus Paragraph 0022: “Movement datasets are preferably sampled at one or more movement sensors indicative of one or more of motion and/or location, which can include one or more of: motion sensors (e.g., multi-axis and/or single-axis accelerometers, gyroscopes, etc.), location sensors (e.g., GPS data collection components, magnetometer, compass, altimeter, etc.)”) (Matus Paragraph 0061: “the first mobile device configured to collect both motion data and GPS location data;”)
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEVIN J HARVEY whose telephone number is 571-272-5327. The examiner can normally be reached 8:00AM-5:00PM M-Th, 8:00AM-4:00PM F.
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/K.J.H./Junior Patent Examiner, Art Unit 3664
/KITO R ROBINSON/Supervisory Patent Examiner, Art Unit 3664
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