Traffic Image-Capturing Unit Network for Vehicle Tracking
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Solution Overview
Problem
Conventional methods for detecting vehicles of interest, such as those involved in crimes, are time-consuming and resource-intensive, relying on ad hoc data processing and requiring extensive analysis of license plate images against databases.
Innovation Solution
A system utilizing a traffic image-capturing unit and a centralized server for dynamic processing of images to detect and track vehicles of interest in real-time, with a dynamic search area module calculating the search radius and trajectory, and selectively engaging image-capturing units to minimize system load and enhance detection speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a license plate scanner is used to capture and process vehicle information against a database, then vehicle detection can be achieved, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The system pre-calculates and stores trajectory information, search areas, and probable locations of vehicles of interest before actual detection is needed. When a vehicle is detected, the system can immediately query pre-computed data rather than performing real-time analysis, significantly reducing processing time while maintaining detection accuracy
Solution Approach 2:
The system dynamically adjusts the scope of search based on the vehicle's trajectory and behavior patterns. Instead of searching all possible locations, the system focuses computational resources on high-probability areas calculated from the vehicle's movement patterns, reducing the search space and processing time while maintaining reliable detection
2Reliability
If multiple image-capturing units are engaged to track a vehicle, then detection coverage is improved, but system load increases and processing speed decreases
Solution Approach 1:
The system assigns different functional roles to different image-capturing units based on their location and the vehicle's trajectory. Only cameras in or near the calculated search area are activated for tracking, while others remain idle. This localized engagement maintains comprehensive detection coverage along the vehicle's path while minimizing the number of active processing units
Solution Approach 2:
The tracking system is divided into multiple independent modules: trajectory calculation, search area determination, camera selection, and active tracking. This segmentation allows the system to process only relevant data through each module, reducing overall system load while maintaining reliable multi-camera coordination when needed
3Reliability
If ad hoc data processing is used to analyze license plate images, then vehicle identification can be performed, but extensive resources are required
Solution Approach 1:
The system pre-processes and stores vehicle trajectory data, search area calculations, and probable location predictions before they are needed for actual detection. This preliminary computation reduces the computational burden during real-time operation, requiring fewer resources while maintaining accurate vehicle identification
Solution Approach 2:
The system extracts and isolates only the critical data elements needed for vehicle identification (such as trajectory, location, and temporal information) from the complete dataset. By removing unnecessary data processing steps and focusing only on essential features, the system reduces computational resource requirements while preserving identification accuracy
Data Source
AI summary
Methods and systems for detecting a vehicle of interest utilizing one or more traffic image-capturing units and a centralized server. A request from an authority to detect a vehicle of interest with respect to an incident can be verified based on particular criteria. One or more of the image-capturing units can be selected along with location information stored in a database in order to enable a search. A notification can be sent to the authority upon identification of the vehicle of interest by the image-capturing unit(s). An area or radius of search can be calculated to alert one or more other image-capturing units for use in tracking the vehicle of interest. Data regarding the vehicle of interest can then be transmitted to an incident management module to dynamically update details regarding detection of the vehicle of interest.