# US 12,217,517 B1 · Apparatus and method for vehicle data analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,217,517 B1 - Document ID: US12217517B1 - Status: Granted - Kind: B1 - Application number: 18/236,634 - Filed: 2023-08-22 - Granted: 2025-02-04 - Earliest claimed: 2023-08-22 - Applicants: EmergIP, LLC - Inventors: Christopher Turner - Web page: https://patentgrep.com/patent/US12217517B1 ## CPC - G06V 20/593: {Recognising seat occupancy} - G06N 3/08: Learning methods - G06N 20/00: Machine learning - G06V 10/764: using classification, e.g. of video objects - G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)} - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE ## Abstract Apparatus and method for vehicle data analysis. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory includes instructions configuring the at least a processor to receive vehicle data from one or more data sources, wherein the vehicle data includes location information that is received from at least a sensor of the one or more data sources and passenger information, classify the vehicle data into one or more vehicle groups, wherein the one or more vehicle groups includes a location group and passenger group, analyze the location group of the one or more vehicle groups to generate a location list, analyze the one or more vehicle groups to generate a passenger list, generate a location report as a function of the location list and generate a passenger report as a function of the passenger list. ## Claims ### Claim 1 An apparatus for vehicle data analysis, the apparatus comprising: at least a processor; and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to: receive a plurality of instances of location information of a plurality of vehicles, wherein each instance of location information describes a destination of a vehicle involved in a traffic accident; categorize the plurality of instances of location information to a plurality of location groups by: determining group training data based on data received from a global positioning system sensor; training a classifier on group training data comprising example location information associated with example location groups; inputting into the classifier an instance of location information of the plurality of instances of location information; receiving as an output from the classifier a categorization of the instance of location information into a location group of the plurality of location groups; updating the group training data as a function of an output of a previous iteration of the classifier; and retraining the classifier based on updated group training data; and generate a location list identifying locations with high accident frequency as a function of the categorization of the plurality of instances of location information. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein: the location group comprises a location group weight; and the memory contains instructions further configuring the at least a processor to generate the location list as a function of the location group weight. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein the processor is further configured to receive accident information comprising contributing factor information indicating potential causes for an accident of the accident information. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein each location group of the plurality of location groups comprises an accident group comprising at least one instance from the plurality of instances at one specific location and locations within a threshold distance. ### Claim 5 (depends on 1) The apparatus of claim 1, wherein the plurality of location groups comprises a plurality of zip groups, wherein each zip group is associated with a specific zip code. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein generating the location list comprises determining a location group weight for each of the plurality of location groups. ### Claim 7 (depends on 6) The apparatus of claim 6, wherein generating the location list comprises arranging the plurality of location groups based on the location group weight for each location group. ### Claim 8 A method for vehicle data analysis, the method comprising: receiving, using at least a processor, a plurality of instances of location information of a plurality of vehicles, wherein each instance of location information describes a destination of a vehicle involved in a traffic accident; categorizing, using the at least a processor, the plurality of instances of location information to a plurality of location groups by: determining group training data based on data received from a global positioning system sensor; training a classifier on group training data comprising example location information associated with example location groups; inputting into the classifier an instance of location information of the plurality of instances of location information; receiving as an output from the classifier a categorization of the instance of location information into a location group of the plurality of location groups; updating the group training data as a function of an output of a previous iteration of the classifier; and retraining the classifier based on updated group training data; and generating, using the at least a processor, a location list identifying locations with high accident frequency as a function of the categorization of the plurality of instances of location information. ### Claim 9 (depends on 8) The method of claim 8, wherein the location list is generated as a function of a location group weight of the one or more vehicle groups. ### Claim 10 (depends on 8) The method of claim 8, further comprising receiving, using the at least a processor, accident information comprising contributing factor information indicating potential causes for an accident of the accident information. ### Claim 11 (depends on 8) The method of claim 8, wherein each location group of the plurality of location groups comprises an accident group comprising at least one instance from the plurality of instances at one specific location and locations within a threshold distance. ### Claim 12 (depends on 8) The method of claim 8, wherein the plurality of location groups comprises a plurality of zip groups, wherein each zip group is associated with a specific zip code. ### Claim 13 (depends on 8) The method of claim 8, wherein generating the location list comprises determining a location group weight for each of the plurality of location groups. ### Claim 14 (depends on 13) The method of claim 13, wherein generating the location list comprises arranging the plurality of location groups based on the location group weight for each location group.