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 .
Claim Rejections - 35 U.S.C. § 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 4, and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (CN105426636 B) in view of Bonnetain ("Unlocking the potential of mobile phone data for large scale urban mobility estimation") and further in view of Takla (US 20210280064 A1).
Consider claim 1, Zhang et al. disclose a system for estimating vehicular pollution, the
system comprising:
one or more processors ("uses a smart phone-based traffic data real-time collection
system" (see Page 5, paragraph 2)); and
one or more computer-readable media storing computer-usable instructions ("The traffic data acquisition system writes an API application program based on the android smartphone operating system" (see Page 5, paragraph 19))
that, when executed by the one or more processors, cause the one or more processors to:
determine a velocity of each UE of the plurality of UEs ("the position information and speed information can be obtained" (see Page 5, paragraph 19)); and
estimate a total number of vehicles in the first location ("In order to obtain the number
of vehicles in the road section and the traffic flow of the section of the road section, the
method of adding the number of vehicles in the parallel cells and the total traffic flow of the
parallel section" (see Page 5, paragraph 14)).
However, Zhang et al. fail to disclose a system that is configured to: receive an indication that a plurality of user equipment (UE) have registered with one or more base station within the telecommunications network; and based on a determination that the velocity of each UE is above a predetermined threshold, determine that each UE is traveling in a vehicle in a first location.
In the same field of endeavor, Bonnetain discloses a system for using mobile phone data
to estimate urban mobility wherein the system is configured to:
receive an indication that a plurality of user equipment (UE) have registered with one or more base station within the telecommunications network (Bonnetain makes reference to recorded network events, which include “handover events (i.e., base station change during an established communication) and network attachment/detachment events” (see Page 4, Section 1.3.1, paragraph 1)); and
based on a determination that the velocity of each UE is above a predetermined threshold, determine that each UE is traveling in a vehicle in a first location (using the trajectory data
collected via the network event tracking approach, “we apply a simple, yet effective, speed-
based heuristic to infer the transportation mode” (see Page 79, Section 4.7, paragraph 1).
From the same dataset, positional data can also be approximated).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to modify the system disclosed by Zhang et al. to use a minimum velocity threshold as taught by Bonnetain in order to filter out data from nonvehicular movement.
However, Zhang et al. as modified by Bonnetain fail to disclose wherein velocity information for the plurality of UEs is aggregated and de-duplicated.
In the same field of endeavor, Takla discloses wherein vehicle velocity information for a plurality of data inputs is aggregated and de-duplicated (see Figure 8, the process 800 “may further include isolating the highest accuracy (CL1) data points and suppress reporting of redundant non-CL1 data (block 815)… V2X communications handler 610 may forward the CL1 data for each vehicle to collision avoidance system 620 and may not forward (e.g., suppress or set aside) CL2 and CL3 data that appear to correspond to the same vehicle as indicated in the CL1 data” (see paragraph 0058). Referring to paragraphs 0053-0054, CL2 and CL3 data may comprise triangulation position data and GPS location information for a mobile communication device, respectively).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to alter the system disclosed by Zhang et al. and modified by Bonnetain to apply the approach of pruning duplicate data collected for singular vehicles taught by Takla, in order to prevent overcounting of vehicles due to the potential for multiple UEs to report data for one vehicle.
Consider claim 4, and as applied to claim 1 above, The combination of Zhang et al., Bonnetain and Takla further disclose wherein velocity of each UE is determined based on a handover time between a UE registering with a first base station and subsequently registering with a second base station or utilizing accelerometric sensor data from the UE (the system “records the data of the GPS module and the acceleration sensor module [of the UE] in real time” to determine vehicle location and velocity (Zhang; see Page 5, paragraph 19)).
Consider claim 7, and as applied to claim 1 above, The combination of Zhang et al., Bonnetain and Takla further disclose wherein the one or more processors is further configured to estimate greenhouse gas emissions for the first location based on the total number of vehicles (“At this point, the emission factors of different types of vehicles can be calculated, combined with the vehicle type look-up table to obtain the emission factors of each pollutant of each type of vehicle, and brought into the source intensity calculation formula, combined with the traffic flow of corresponding types of vehicles…the formula adds the same pollutants emitted by different types of vehicles, and finally obtains the total emissions of different pollutants in the road section” (Zhang; see Page 8, paragraph 15)).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al.
(CN105426636 B) in view of Bonnetain (“Unlocking the potential of mobile phone data for
large scale urban mobility estimation”) and further in view of Takla (US 20210280064 A1) and Choueifaty et al. (US 10373172 B2).
Consider claim 2, and as applied to claim 1 above, Zhang et al. as modified by Bonnetain and Takla fail to disclose wherein each UE includes any equipment that uses a chip card and a chip.
In the same field of endeavor, Choueifaty et al. disclose a system for monitoring vehicle emissions wherein the UE includes any equipment that uses a chip card and a chip (referring to Figure 2c, “The automobile 52 may include various units/modules or elements which are configured to implement and/or perform at least some of the different operations/steps illustrated in FIGS. 2a and 2b, such as: a communication module comprising a transmission unit 52a and a receiving unit 52b (e.g. a SIM card embedded in the car electronic system)” (see Figure 2c, Column 29, line 23-29)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to modify the system disclosed by the combination of Zhang et al., Bonnetain and Takla by implementing a UE that uses a chip card and a chip equipment as disclosed by Choueifaty in
order to permit the UE to access a telecommunications network for data collection purposes.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (CN105426636 B) in view of Bonnetain (“Unlocking the potential of mobile phone data for large scale urban mobility estimation”) and further in view of Takla (US 20210280064 A1) and Thibault et al. (US 20140031061 A1).
Consider claim 3, and as applied to claim 1 above, Zhang et al. as modified by Bonnetain and Takla fail to disclose a system wherein the predetermined threshold to determine a vehicle is in motion is 10 miles per hour.
In the same field of endeavor, Thibault et al. disclose a system for monitoring a vehicle wherein the predetermined threshold to determine a vehicle is in motion is 10 miles per hour (“In an aspect, it can be detected whether the device 102a is in a moving vehicle…the speed threshold to determine a moving vehicle can be a low speed (e.g., 10 MPH)” (see paragraph 0033)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to modify the system disclosed by the combination of Zhang et al., Bonnetain and Takla by implementing a predetermined movement threshold of 10 miles per hour as disclosed in Thibault et al., in order to exclude extraneous data collected from non-vehicular movement.
Claims 5 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al.
(CN105426636 B) in view of Bonnetain (“Unlocking the potential of mobile phone data for large scale urban mobility estimation”) and further in view of Takla (US 20210280064 A1) and Sanchez (WO 2021195059 A1).
Consider claim 5, and as applied to claim 1 above, Zhang et al. as modified by Bonnetain and Takla fail to disclose a system further comprising communicating vehicle information to the telecommunications network including a make and model of the vehicle.
In the same field of endeavor, Sanchez discloses a system providing renewing carbon offsets for a driving period of a user comprising communicating vehicle information to the telecommunications network including a make and model of the vehicle (Process 100 in Figure 1A includes “estimating the amount of total carbon emission of the user’s driving period is based upon fuel-consumption driving data and/or vehicle information collected for the one or more vehicle trips made by the user… For example, the vehicle information indicate various specifications of the vehicle operated by the user, such as model/year/make” (see paragraph 0029). System 200 in Figure 2 implements the method 100, and in one embodiment “the server 206 includes various software applications stored in the memory 232 and executable by the processor 230. For example, these software applications include specific
programs, routines, or scripts for performing functions associated with the method 100” (see paragraph 0052). It is reasonable to assume one of these functions is the estimation for the amount of total carbon emission, which would require vehicle specifications such as make and model to be communicated to the server via the network 204).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the system disclosed by the combination of Zhang et al., Bonnetain and Takla by implementing a technique to communicate vehicle information to the telecommunications network including a make and model of the vehicle as disclosed by Sanchez in order to more accurately calculate the emissions output unique to each vehicle.
Consider claim 6, and as applied to claim 1 above, Zhang et al. as modified by Bonnetain and Takla fail to disclose wherein the one or more processors is further configured to communicate vehicle information to a data storage to maintain and store the vehicle information.
In the same field of endeavor, Sanchez discloses wherein the one or more processors is further configured to communicate vehicle information to a data storage to maintain and store the vehicle information (“the vehicle information are identified using a unique identifier of the vehicle (e.g., vehicle identification number (VIN)), which may be supplied by the user or collected from a manufacturer of the vehicle” (see paragraph 0032). Referring to Figure 2, data is collected on “various operating parameters of the vehicle, such as speed, acceleration, braking, location, engine status, fuel level, as well as other suitable parameters…According to certain embodiments, the collected data are stored in the memory 218 before being transmitted to the server 206 using the communications unit 220 via the network 204” (see Figure 2, paragraph 0052). The described vehicle information can reasonably be assumed to be part of this transmission, given that the described vehicle information is integral to the calculation of emissions and that said calculation takes place on the server side (see paragraph 0054)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the system disclosed by the combination of Zhang et al., Bonnetain and Takla by implementing a technique wherein the one or more processors is further configured to communicate vehicle information to a data storage to maintain and store the vehicle information as disclosed by Sanchez in order to apply these parameters to subsequent usage data from the same vehicle.
Allowable Subject Matter
Claims 8-12, 14-19, and 21-22 are allowed and renumbered as claims 8-20, respectively. All previous rejections are withdrawn.
The following is an Examiner’s statement of reasons for allowance:
Consider claims 8 and 15, the best prior art references found during examination for the present application were Zhang et al. (CN105426636 B), Bonnetain ("Unlocking the potential of mobile phone data for large scale urban mobility estimation"), and Thibault (US 20140031061 A1).
Consider claim 8, Zhang et al. disclose a method for measuring greenhouse gas emissions utilizing a telecommunications network, the method comprising: determining a total number of vehicles at a first location (“obtain[ing] the number of vehicles in the road section and the traffic flow of the section of the road section” (see Page 5, paragraph 14) using positional and speed information which are obtained via a GPS module); and
based on the total number of vehicles, estimating greenhouse gas emissions for the first location (“At this point, the emission factors of different types of vehicles can be calculated, combined with the vehicle type look-up table to obtain the emission factors of each pollutant of each type of vehicle, and brought into the source intensity calculation formula, combined with the traffic flow of corresponding types of vehicles…the formula adds the same pollutants emitted by different types of vehicles, and finally obtains the total emissions of different pollutants in the road section” (see Page 8, paragraph 15)).
However, Zhang et al. fail to disclose a method comprising identifying a plurality of user equipment (UE) devices moving at a velocity above a predetermined threshold.
In the same field of endeavor, Bonnetain discloses a method comprising: identifying a plurality of user equipment (UE) devices moving at a velocity above a predetermined threshold (using the trajectory data collected via the network event tracking approach, “we apply a simple, yet effective, speed-based heuristic to infer the transportation mode” (see Page 79, Section 4.7, paragraph 1). From the same dataset, positional data for a plurality of UE devices can also be approximated);
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Zhang et al. by configuring it to identify a plurality of UE devices moving at a velocity above a predetermined threshold as disclosed in Bonnetain in order to filter out data from nonvehicular movement.
However, Zhang et al. as modified by Bonnetain fail to disclose a method comprising: based on the velocity above the predetermined threshold, determining that the plurality of UE devices is moving in one or more vehicles and determining a total number of vehicles in a first location based on analyzing one or more occupancy criteria, wherein the one or more occupancy criteria comprises a velocity for each UE device of the plurality of UE devices.
In the same field of endeavor, Thibault et al. disclose a method comprising: based on the velocity above a predetermined threshold, determining that the plurality of UE devices is moving in one or more vehicles (referring to Figure 1, “it can be detected whether the device 102a is in a moving vehicle. For example, based on one or more of speed, location, direction of movement, proximity, motion sensing device sensitivity, type of device and paths of known roads near the device 102a…Moreover, the same detection mechanism can be used to determine whether two or more devices are likely to be in the same vehicle, based on the speed, location, direction of movement, proximity, and paths of known roads near the devices” (see paragraph 0033));
determining a total number of vehicles in a first location based on analyzing one or more occupancy criteria, wherein the one or more occupancy criteria comprises a velocity for each UE device of the plurality of UE devices (Zhang et al. discusses “obtain[ing] the number of vehicles in the road section and the traffic flow of the section of the road section” (see Page 5, paragraph 14) using positional and speed information which are obtained via a GPS module. Thibault et al. discloses analyzing velocity data for multiple UEs in the same vehicle (see paragraph 0033)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Zhang et al. and modified by Bonnetain by using velocity information to assess the total number of vehicles in an area as disclosed by Thibault et al. in order to avoid overcounting the total number of vehicles in one location.
However, neither Zhang et al., Bonnetain, Thibault et al., nor any other cited prior art reference disclose a method wherein determining the total number of vehicles comprises grouping the plurality of UE devices into sets based on velocities of the UE devices being within a threshold range and distances between the UE devices being below a distance threshold and determining the total number of vehicles based on a number of the sets.
Consider claim 15, Zhang et al. disclose a system for measuring vehicular greenhouse
gas emissions, the system comprising:
one or more processors (“uses a smart phone-based traffic data real-time collection system” (see Page 5, paragraph 2)); and
one or more computer-readable media storing computer-usable instructions (“The traffic data acquisition system writes an API application program based on the android smartphone operating system” (see Page 5, paragraph 19)) that, when executed by the one or more processors, cause the one or more processors to:
determine a total number of vehicles at a first location (“obtain[ing] the number of vehicles in the road section and the traffic flow of the section of the road section” (see Page 5, paragraph 14) using positional and speed information which are obtained via a GPS module); and
based on the total number of vehicles, estimate greenhouse gas emissions for the first location (“At this point, the emission factors of different types of vehicles can be calculated, combined with the vehicle type look-up table to obtain the emission factors of each pollutant of each type of vehicle, and brought into the source intensity calculation formula, combined with the traffic flow of corresponding types of vehicles…the formula adds the same pollutants emitted by different types of vehicles, and finally obtains the total emissions of different pollutants in the road section” (see Page 8, paragraph 15)).
However, Zhang et al. fail to disclose a system that is configured to identify a plurality of user equipment (UE) devices moving at a velocity above a predetermined threshold.
In the same field of endeavor, Bonnetain discloses a system comprising: identifying a plurality of user equipment (UE) devices moving at a velocity above a predetermined threshold (using the trajectory data collected via the network event tracking approach, “we apply a simple, yet effective, speed-based heuristic to infer the transportation mode” (see Page 79, Section 4.7, paragraph 1). From the same dataset, positional data for a plurality of UE devices can also be approximated);
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the system disclosed by Zhang et al. by configuring it to identify a plurality of UE devices moving at a velocity above a predetermined threshold as disclosed in Bonnetain in order to filter out data from nonvehicular movement.
However, Zhang et al. as modified by Bonnetain fail to disclose a system comprising determining based on the velocity above a predetermined threshold that the plurality of UE devices is moving in one or more vehicle and determining a total number of vehicles in a first location based on analyzing one or more occupancy criteria, wherein the one or more occupancy criteria comprises a velocity for each UE device of the plurality of UE devices.
In the same field of endeavor, Thibault et al. disclose a system configured to: based on the velocity above a predetermined threshold, determine that the plurality of UE devices is moving in a vehicle (referring to Figure 1, “it can be detected whether the device 102a is in a moving vehicle. For example, based on one or more of speed, location, direction of movement, proximity, motion sensing device sensitivity, type of device and paths of known roads near the device 102a…Moreover, the same detection mechanism can be used to determine whether two or more devices are likely to be in the same vehicle, based on the speed, location, direction of movement, proximity, and paths of known roads near the devices” (see paragraph 0033));
determine a total number of vehicles at a first location based on analyzing one or more occupancy criteria, wherein the one or more occupancy criteria comprises a velocity for each UE device of the plurality of UE devices (Zhang et al. discusses “obtain[ing] the number of vehicles in the road section and the traffic flow of the section of the road section” (see Page 5, paragraph 14) using positional and speed information which are obtained via a GPS module. Thibault et al. discloses analyzing velocity data for multiple UEs in the same vehicle (see paragraph 0033)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Zhang et al. and modified by Bonnetain by using velocity information to assess the total number of vehicles in an area as disclosed by Thibault et al. in order to avoid overcounting the total number of vehicles in one location.
However, neither Zhang et al., Bonnetain, Thibault et al., nor any other cited prior art reference disclose a system wherein determining the total number of vehicles comprises grouping the plurality of UE devices into sets based on velocities of the UE devices being within a threshold range and distances between the UE devices being below a distance threshold and determining the total number of vehicles based on a number of the sets.
Dependent claims 8-12, 14, 16-19, and 21-22 are allowed by virtue of their dependency on claims 8 and 15.
Response to Arguments
Applicant’s arguments with respect to claims 1-7 have been considered but are moot because of the new ground of rejection.
Applicant’s arguments/amendments, with respect to claims 8-12, 14-19, 21, and 22 have been fully considered and are persuasive. The 103 Rejections have been withdrawn. Please refer to the Allowable Subject Matter section above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ALEXANDER WU/Examiner, Art Unit 2642
/ANTHONY S ADDY/Supervisory Patent Examiner, Art Unit 2645
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