Abstract: Disclosed herein are methods, systems, and apparatus for automated license plate recognition and methods for training a machine learning model to undertake automated license plate recognition. For example, a method can comprise dividing an image or video frame comprising a license plate into a plurality of image patches, determining a positional vector for each of the image patches, adding the positional vector to each of the image patches and inputting the image patches and their associated positional vectors to a text-adapted vision transformer. The text-adapted vision transformer can be configured to output a prediction concerning the license plate number of the license plate.

Abstract: Disclosed herein are methods and systems for managing traffic violation or enforcement data using a distributed ledger. The distributed ledger provides a transparent chain of custody/evidence related to all digital interactions with traffic violation or enforcement data. The distributed ledger can be audited for data accuracy and integrity by nodes making up the system each time one of the nodes interacts with the traffic violation or enforcement data. For example, a digital evidence package related to a traffic violation event can be generated by a node within the system and a package digest can be logged in the distributed ledger beginning with the creation of the digital evidence package and each time that the digital evidence package is processed, modified, or reviewed by nodes within the system.

Abstract: Disclosed herein are systems, methods, and devices for detecting traffic lane violations. In one embodiment, a method for detecting a potential traffic violation is disclosed comprising bounding a vehicle detected from one or more video frames of a video in a vehicle bounding box. The vehicle can be detected and bounded using a first convolutional neural network. The method can also comprise bounding, using the one or more processors of the edge device, a plurality of lanes of a roadway detected from the one or more video frames in a plurality of polygons. The plurality of lanes can be detected and bounded using multiple heads of a multi-headed second convolutional neural network. The method can further comprise detecting a potential traffic violation based in part on an overlap of at least part of the vehicle bounding box and at least part of one of the polygons.

Abstract: Disclosed herein are systems and methods for managing traffic rules. In one embodiment, a method of managing traffic rules can comprise generating or updating a semantic map layer based in part on positioning data obtained from one or more edge devices and videos captured by the one or more edge devices. The method can also comprise generating or updating a traffic enforcement layer on top of the semantic map layer. A plurality of traffic rules can be saved as part of the traffic enforcement layer. The method can further comprise generating or updating a traffic insight layer based in part on traffic violations or traffic conditions determined by the one or more edge devices or the server. The traffic insight layer can adjust or provide a suggestion to adjust at least one of the traffic rules based on an impact analysis conducted by the traffic insight layer concerning the traffic rule.

Abstract: Disclosed are systems and methods for detecting traffic violations using one or more mobile detection devices. Videos captured by one or more mobile detection devices can be processed on the mobile detection devices to extract data and information concerning a potential traffic violation involving a vehicle and a restricted road area. The mobile detection devices can transmit such data and information to a server configured to make a determination as to whether a traffic violation has occurred by comparing the data and information received from the mobile detection devices.

Abstract: Disclosed herein are methods and systems for managing traffic violation or enforcement data using a distributed ledger. The distributed ledger provides a transparent chain of custody/evidence related to all digital interactions with traffic violation or enforcement data. The distributed ledger can be audited for data accuracy and integrity by nodes making up the system each time one of the nodes interacts with the traffic violation or enforcement data. For example, a digital evidence package related to a traffic violation event can be generated by a node within the system and a package digest can be logged in the distributed ledger beginning with the creation of the digital evidence package and each time that the digital evidence package is processed, modified, or reviewed by nodes within the system.

Abstract: Disclosed herein are methods and systems for managing traffic violation or enforcement data using a distributed ledger. The distributed ledger provides a transparent chain of custody/evidence related to all digital interactions with traffic violation or enforcement data. The distributed ledger can be audited for data accuracy and integrity by nodes making up the system each time one of the nodes interacts with the traffic violation or enforcement data. For example, a digital evidence package related to a traffic violation event can be generated by a node within the system and a package digest can be logged in the distributed ledger beginning with the creation of the digital evidence package and each time that the digital evidence package is processed, modified, or reviewed by nodes within the system.

Abstract: Disclosed herein are systems, methods, and devices for detecting traffic lane violations. In one embodiment, a method for detecting a potential traffic violation is disclosed comprising bounding a vehicle detected from one or more video frames of a video in a vehicle bounding box. The vehicle can be detected and bounded using a first convolutional neural network. The method can also comprise bounding, using the one or more processors of the edge device, a plurality of lanes of a roadway detected from the one or more video frames in a plurality of polygons. The plurality of lanes can be detected and bounded using multiple heads of a multi-headed second convolutional neural network. The method can further comprise detecting a potential traffic violation based in part on an overlap of at least part of the vehicle bounding box and at least part of one of the polygons.

Abstract: Disclosed are systems and methods for detecting traffic violations using one or more mobile detection devices. Videos captured by one or more mobile detection devices can be processed on the mobile detection devices to extract data and information concerning a potential traffic violation involving a vehicle and a restricted road area. The mobile detection devices can transmit such data and information to a server configured to make a determination as to whether a traffic violation has occurred by comparing the data and information received from the mobile detection devices.

Abstract: Disclosed herein are systems and apparatus for detecting a traffic violation. In one embodiment, a system for detecting a traffic violation comprises a context camera assembly and a license plate recognition (LPR) camera assembly. The context camera assembly can comprise a context camera housing containing a context camera, a context camera mount configured to mount the context camera housing to an interior of a carrier vehicle, and a context camera skirt coupled to and protruding outwardly from the context camera housing. The license LPR camera assembly can comprise an LPR camera housing containing one or more LPR cameras, an LPR camera mount configured to mount the LPR camera housing to the interior of the carrier vehicle, and one or more LPR camera skirts coupled to and protruding outwardly from the LPR camera housing.

Abstract: Disclosed herein are methods and systems that allow users to report traffic violations and obtain information concerning reported violations using mobile devices. In one embodiment, a method comprises receiving, at a server, one or more images or videos captured by a mobile device of an offending vehicle committing a potential traffic violation and an extended metadata tag; storing the one or more images or videos and the extended metadata tag as unstructured content in a content lake; generating database tables on top of the content lake; receiving a request from another mobile device to view traffic violation content; querying the database tables and retrieving at least one of the one or more images or videos of the offending vehicle committing the potential traffic violation from the content lake; and generating a GUI to be displayed via the other mobile device showing the traffic violation content.

Abstract: Disclosed herein are methods and systems that allow users to report traffic violations and obtain information concerning reported violations using mobile devices. In one embodiment, a method comprises receiving, at a server, one or more images or videos captured by a mobile device of an offending vehicle committing a potential traffic violation and an extended metadata tag; storing the one or more images or videos and the extended metadata tag as unstructured content in a content lake; generating database tables on top of the content lake; receiving a request from another mobile device to view traffic violation content; querying the database tables and retrieving at least one of the one or more images or videos of the offending vehicle committing the potential traffic violation from the content lake; and generating a GUI to be displayed via the other mobile device showing the traffic violation content.

Abstract: Disclosed herein are systems and methods for managing traffic rules. In one embodiment, a method of managing traffic rules can comprise generating or updating a semantic map layer based in part on positioning data obtained from one or more edge devices and videos captured by the one or more edge devices. The method can also comprise generating or updating a traffic enforcement layer on top of the semantic map layer. A plurality of traffic rules can be saved as part of the traffic enforcement layer. The method can further comprise generating or updating a traffic insight layer based in part on traffic violations or traffic conditions determined by the one or more edge devices or the server. The traffic insight layer can adjust or provide a suggestion to adjust at least one of the traffic rules based on an impact analysis conducted by the traffic insight layer concerning the traffic rule.

Abstract: Disclosed herein are systems and methods for managing traffic rules. In one embodiment, a method of managing traffic rules can comprise generating or updating a semantic map layer based in part on positioning data obtained from one or more edge devices and videos captured by the one or more edge devices. The method can also comprise generating or updating a traffic enforcement layer on top of the semantic map layer. A plurality of traffic rules can be saved as part of the traffic enforcement layer. The method can further comprise generating or updating a traffic insight layer based in part on traffic violations or traffic conditions determined by the one or more edge devices or the server. The traffic insight layer can adjust or provide a suggestion to adjust at least one of the traffic rules based on an impact analysis conducted by the traffic insight layer concerning the traffic rule.

Abstract: Disclosed are systems and methods for detecting traffic violations using one or more mobile detection devices. Videos captured by one or more mobile detection devices can be processed on the mobile detection devices to extract data and information concerning a potential traffic violation involving a vehicle and a restricted road area. The mobile detection devices can transmit such data and information to a server configured to make a determination as to whether a traffic violation has occurred by comparing the data and information received from the mobile detection devices.

Abstract: Disclosed herein are systems, methods, and devices for detecting traffic lane violations. In one embodiment, a method for detecting a potential traffic violation is disclosed comprising bounding a vehicle detected from one or more video frames of a video in a vehicle bounding box. The vehicle can be detected and bounded using a first convolutional neural network. The method can also comprise bounding, using the one or more processors of the edge device, a plurality of lanes of a roadway detected from the one or more video frames in a plurality of polygons. The plurality of lanes can be detected and bounded using multiple heads of a multi-headed second convolutional neural network. The method can further comprise detecting a potential traffic violation based in part on an overlap of at least part of the vehicle bounding box and at least part of one of the polygons.