# US 2025/0095378 A1 · Vehicle recognition systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0095378 A1 - Document ID: US20250095378A1 - Status: Published application - Kind: A1 - Application number: 18/885,678 - Filed: 2024-09-15 - Published: 2025-03-20 - Earliest claimed: 2023-09-15 - Assignees: NxtWash, LLC - Applicants: NxtWash, LLC - Inventors: Justin Ruelas; David Selsberg; Dorjan Hajdari - Web page: https://patentgrep.com/patent/US20250095378A1 ## CPC - G06V 20/54: of traffic, e.g. cars on the road, trains or boats - G01J 5/00: Radiation pyrometry, e.g. infrared or optical thermometry - G06V 10/82: using neural networks - G06V 20/625: {License plates} - G06V 30/10: Character recognition - G08G 1/0175: {by photographing vehicles, e.g. when violating traffic rules} - G01J 2005/0077: {Imaging} - G06V 2201/08: Detecting or categorising vehicles - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G01J: MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY (light sources F21, H01J, H01K, H05B; investigating properties of materials by optical means G01N) - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) ## Abstract Methods and systems are described, including receiving, at a server from a computing device associated with at least one camera, at least one image of a vehicle detected in a vehicle detection zone during a first time period, generating, using the at least one image, a prediction of at least one data object associated with the vehicle, determining whether the prediction of the at least one data object matches a vehicle profile, and communicating a result of determining whether the prediction of the prediction matches the vehicle profile. The methods and systems may include creating, based on determining that the prediction of the at least one data object fails to match the vehicle profile, a new vehicle profile for the vehicle including at least one descriptor corresponding to the at least one data object and assigning a vehicle token to the vehicle profile. ## Claims ### Claim 1 A method for data processing, comprising: receiving, at a server and from a computing device associated with a camera, at least one image of a vehicle detected in a vehicle detection zone during a first time period; generating, using the at least one image, a prediction of at least one data object associated with the vehicle; determining whether the prediction of the at least one data object matches a vehicle profile from a vehicle profile data store; and communicating a result of determining whether the prediction of the at least one data object matches the vehicle profile. ### Claim 2 (depends on 1) The method of claim 1, further comprising: creating, based at least in part on determining that the prediction of the at least one data object fails to match the vehicle profile, a new vehicle profile for the vehicle comprising at least one descriptor corresponding to the at least one data object; and assigning a vehicle token to the vehicle profile, wherein communicating the result comprises storing the vehicle profile in a data store. ### Claim 3 (depends on 1) The method of claim 1, wherein generating the prediction of the at least one data object comprises: transmitting, to one or more vehicle identification services, the at least one image of the vehicle; and generating, by the one or more vehicle identification services, a predicted license plate string identified from the at least one image, wherein the prediction comprises the predicted license plate string and a confidence score associated with the prediction of the predicted license plate string. ### Claim 4 (depends on 3) The method of claim 3, wherein determining whether the prediction of the at least one data object matches the vehicle profile comprises: determining, based at least in part on the confidence score being greater than a threshold, whether the predicted license plate string matches a license plate string in a plurality of vehicle profiles in the vehicle profile data store. ### Claim 5 (depends on 3) The method of claim 3, wherein determining whether the prediction of the at least one data object matches the vehicle profile comprises: determining, that the confidence score is less than a threshold; identifying a subset of vehicle profiles of a plurality of vehicle profiles in the vehicle profile data store that have a license plate string length that matches a license plate string length of the predicted license plate string; and determining whether a threshold quantity of characters are matched between the predicted license plate string and respective license plate strings of the subset of vehicle profiles. ### Claim 6 (depends on 5) The method of claim 5, further comprising: determining, based at least in part on a threshold quantity of characters being matched, whether at least one additional data object prediction from the at least one image of the vehicle and comprising a make, model, or color, matches corresponding data objects of the subset of vehicle profiles, wherein the at least one additional data object is received from the one or more vehicle identification services. ### Claim 7 (depends on 5) The method of claim 5, wherein the threshold quantity is based on the license plate string length. ### Claim 8 (depends on 5) The method of claim 5, wherein the one or more vehicle identification services are configured to return a prediction of at least one of a make of the vehicle and a model of the vehicle, using a vehicle identification procedure that comprises: identifying a feature of the vehicle; drawing reference points on each feature; measuring a respective distance between each pair of reference points; generating a point distance ratio from the respective distances between each pair of reference points; and generating the prediction of at least one of the make of the vehicle and the model of the vehicle, based at least in part on the point distance ratio. ### Claim 9 (depends on 1) The method of claim 1, wherein communicating the result of comprises: transmitting, to the computing device, at least one of an identifier for the matched vehicle profile and an identifier for a generated new vehicle profile. ### Claim 10 (depends on 1) The method of claim 1, wherein generating the prediction comprises: detecting, based at least at in part on one or more heat signatures included in the at least one image that comprises a thermal image captured by the camera that comprises a thermal camera, identifiable features of the vehicle; and generating the prediction based at least in part on the identifiable features of the vehicle. ### Claim 11 (depends on 10) The method of claim 10, wherein the identifiable features comprises hood structure of a hood of the vehicle. ### Claim 12 (depends on 1) The method of claim 1, wherein communicating the result comprises: communicating, to the computing device, an identifier for the vehicle, wherein the computing device is configured to perform one or more actions based at least in part on the identifier. ### Claim 13 An apparatus for data processing, comprising: one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the apparatus to: receive, at a server and from a computing device associated with at least one camera, at least one image of a vehicle detected in a vehicle detection zone during a first time period; generate, using the at least one image, a prediction of at least one data object associated with the vehicle; determine whether the prediction of the at least one data object matches a vehicle profile from a vehicle profile data store; and communicate a result of determining whether the prediction of the at least one data object matches the vehicle profile. ### Claim 14 (depends on 13) The apparatus of claim 13, wherein the one or more processors are individually or collectively further operable to execute the code to cause the apparatus to: create, based at least in part on determining that the prediction of the at least one data object fails to match the vehicle profile, a new vehicle profile for the vehicle comprising at least one descriptor corresponding to the at least one data object; and assign a vehicle token to the vehicle profile, wherein communicating the result comprises storing the vehicle profile in a data store. ### Claim 15 (depends on 13) The apparatus of claim 13, wherein, to generate the prediction of the at least one data object, the one or more processors are individually or collectively operable to execute the code to cause the apparatus to: transmit, to one or more vehicle identification services, the at least one image of the vehicle; and generating, by the one or more vehicle identification services, a predicted license plate string identified from the at least one image, wherein the prediction comprises the predicted license plate string and a confidence score associated with the prediction of the predicted license plate string. ### Claim 16 (depends on 15) The apparatus of claim 15, wherein, to determine whether the prediction of the at least one data object matches the vehicle profile, the one or more processors are individually or collectively operable to execute the code to cause the apparatus to: determine, based at least in part on the confidence score being greater than a threshold, whether the predicted license plate string matches a license plate string in a plurality of vehicle profiles in the vehicle profile data store. ### Claim 17 (depends on 15) The apparatus of claim 15, wherein, to determine whether the prediction of the at least one data object matches the vehicle profile, the one or more processors are individually or collectively operable to execute the code to cause the apparatus to: determine, that the confidence score is less than a threshold; identify a subset of vehicle profiles of a plurality of vehicle profiles in the vehicle profile data store that have a license plate string length that matches a license plate string length of the predicted license plate string; and determine whether a threshold quantity of characters are matched between the predicted license plate string and respective license plate strings of the subset of vehicle profiles. ### Claim 18 A non-transitory computer-readable medium storing code for data processing, the code comprising instructions executable by one or more processors to: receive, at a server and from a computing device associated with at least one camera, at least one image of a vehicle detected in a vehicle detection zone during a first time period; generate, using the at least one image, a prediction of at least one data object associated with the vehicle; determine whether the prediction of the at least one data object matches a vehicle profile from a vehicle profile data store; and communicate a result of determining whether the prediction of the at least one data object matches the vehicle profile. ### Claim 19 (depends on 18) The non-transitory computer-readable medium of claim 18, wherein the code is further executable by the one or more processors to: create, based at least in part on determining that the prediction of the at least one data object fails to match the vehicle profile, a new vehicle profile for the vehicle comprising at least one descriptor corresponding to the at least one data object; and assign a vehicle token to the vehicle profile, wherein communicating the result comprises storing the vehicle profile in a data store. ### Claim 20 (depends on 18) The non-transitory computer-readable medium of claim 18, wherein the code to generate the prediction of the at least one data object are executable by the one or more processors to: transmit, to one or more vehicle identification services, the at least one image of the vehicle; and receive, from the one or more vehicle identification services, a prediction of a license plate string identified from the at least one image, wherein the prediction comprises the license plate string and a confidence score associated with the prediction of the license plate string.