Vehicle Sensor Data Selection for Event Investigation
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Solution Overview
Problem
Current systems for investigating events using onboard vehicle sensors, such as dash cams, are inefficient due to reliance on civilian operators with little law enforcement experience, leading to irrelevant data submissions and impractical data collection and processing from multiple vehicles.
Innovation Solution
A system that utilizes spatiotemporal information from vehicles equipped with sensors to selectively request and retrieve relevant data from specific vehicles, employing cognitive analysis and machine learning to identify and track entities of interest, thereby optimizing data collection and analysis for event investigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all data from every relevant vehicle is collected, then the completeness of event investigation data is improved, but the complexity and impracticality of data collection, maintenance, and processing increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing spatiotemporal information from vehicles before an event occurs. When an event is reported, the system can immediately query and retrieve relevant data without needing to collect anything at that moment, thus avoiding the complexity of real-time comprehensive data collection while ensuring data completeness.
Solution Approach 2:
The system extracts only the necessary spatiotemporal information (location, time, sensor data) from vehicles that is relevant to event investigation, rather than collecting and processing all possible vehicle data. This selective extraction reduces the burden of data management while maintaining investigation effectiveness.
2Ease of operation
If data is selected and submitted by civilian drivers, then the ease of data submission is improved, but the relevance and usefulness of the submitted data deteriorates
Solution Approach 1:
The system provides feedback to civilian drivers by automatically querying them for specific data based on reported events. Instead of relying on drivers to independently judge what data is relevant, the system uses the reported event details (location, time) to identify and request specific spatiotemporal data from vehicles that were present at the event, thereby ensuring data relevance while maintaining ease of submission.
Solution Approach 2:
The system acts as an intermediary between the event reporting authority and civilian drivers. It receives event information, processes it to identify relevant vehicles, and then automatically requests data from those vehicles. This intermediary role eliminates the need for drivers to make judgment calls about data relevance, improving both relevance and ease of operation.
Data Source
AI summary
Embodiments for utilizing vehicles to investigate events are provided. Spatiotemporal information is received from each of a plurality of vehicles. Each of the plurality of vehicles includes an onboard sensor. Information associated with an event is received. At least some of the plurality of vehicles are selected based on the information associated with the event and the spatiotemporal information from each of a plurality of vehicles. A request is caused to be transmitted to each of the selected at least some of the plurality of vehicles for data detected by the respective onboard sensor.