Vehicle Image Analysis for Abnormal Condition Detection
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Solution Overview
Problem
Current vehicle technologies are inadequate in detecting abnormal operation conditions, such as unauthorized operators or unattended children, which can compromise safety and violate regulations, as they lack the ability to analyze image data to identify and communicate such anomalies.
Innovation Solution
A system comprising image sensors, processors, and transceivers that capture and analyze image frames to detect abnormal conditions within vehicles, such as unauthorized operators or excessive occupancy, and generate notifications to associated electronic devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image sensors and image analysis techniques are implemented to detect abnormal vehicle conditions, then the ability to identify unauthorized operators or unattended children is improved, but the device complexity increases
Solution Approach 1:
The system segments the detection task into distinct modules: image capture by sensors, face detection algorithms, abnormal condition identification, and notification generation. This modular approach improves detection precision while managing complexity through functional separation.
Solution Approach 2:
The patent introduces an intermediary processing system that bridges the gap between simple image capture and complex abnormal condition detection. The processor acts as an intermediary, analyzing image data and translating it into actionable detection results without requiring the entire system to be simultaneously complex.
2Reliability
If image analysis is performed continuously to detect abnormal conditions, then the reliability of safety monitoring is improved, but the energy consumption increases
Solution Approach 1:
The system employs periodic action by capturing images at regular intervals rather than continuous monitoring. The processor analyzes image frames periodically to detect abnormal conditions, maintaining safety monitoring reliability while significantly reducing energy consumption compared to continuous analysis.
Solution Approach 2:
The image analysis system performs self-service by automatically detecting abnormal conditions and generating notifications without requiring constant external intervention. The system monitors itself and takes corrective action (sending notifications) only when abnormalities are detected, optimizing energy usage.
3Measurement precision
If face detection and analysis are implemented in image frames, then the precision of identifying individual conditions is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system performs preliminary action by pre-processing image frames to identify and isolate face regions before conducting detailed analysis. Face detection algorithms prepare the data by locating facial features in advance, which simplifies subsequent abnormal condition analysis and reduces overall detection difficulty.
Data Source
AI summary
Systems and methods for using image analysis techniques to assess abnormal vehicle operating conditions are disclosed. According to aspects, a computing device may access and analyze image data depicting an individual(s) within a vehicle. Based on the depicted individuals(s) and optionally on other data, the computing device may determine that an abnormal condition exists. In response, the computing device may generate a notification and transmit the notification to an electronic device of an individual associated with the vehicle.