Fuel Theft Detection Using Multi-Sensor Confidence Thresholds
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Solution Overview
Problem
Existing systems for preventing fuel theft from vehicles, such as fuel cap locks and anti-siphon devices, are inadequate as thieves can easily circumvent them, leading to significant financial losses.
Innovation Solution
A theft prevention system that includes sensors to detect suspicious activity near the fuel tank, determines confidence values based on motion and video/audio analysis, and triggers alarms or alerts when certain thresholds are met, with varying levels of mitigation actions based on confidence values and driver proximity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simple mechanical measures like fuel cap locks and anti-siphon devices are used, then device complexity is reduced, but theft prevention reliability is insufficient
Solution Approach 1:
The system divides theft prevention into multiple independent detection layers: motion detection, video analysis, audio analysis, and fluid level monitoring. Each layer operates independently and contributes to the overall confidence score, allowing the system to maintain high reliability without requiring a single complex mechanism
Solution Approach 2:
The sensing system performs multiple functions simultaneously: detecting motion, analyzing video for suspicious objects/tools, analyzing audio for drilling sounds, and monitoring fluid levels. This multi-functional approach increases theft prevention reliability without proportionally increasing device complexity
2Reliability
If continuous monitoring with low confidence threshold is used, then theft detection capability is improved, but false alarm rate increases
Solution Approach 1:
The confidence threshold is not fixed but dynamically adjusted based on the combination of multiple detection factors. The system calculates an overall confidence score by combining results from motion detection, video analysis, audio analysis, and fluid level changes, allowing flexible adaptation to different threat scenarios while maintaining accurate theft detection
Solution Approach 2:
The system continuously monitors multiple parameters and provides feedback to adjust the confidence score. When multiple independent detection methods indicate suspicious activity simultaneously, the confidence score increases, reducing false alarms while maintaining high theft detection accuracy
3Measurement precision
If multiple sensing systems and analysis methods are deployed, then theft detection accuracy is improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent combines multiple sensing systems (motion sensors, video cameras, audio sensors, fluid level sensors) into a unified theft prevention system that shares common processing logic and confidence score calculation. This merging approach maintains high detection accuracy while reducing overall system complexity through shared components and centralized control
4Measurement precision
If multiple sensing systems are continuously activated, then detection capability is improved, but energy consumption increases
Solution Approach 1:
The system activates different sensing systems periodically or on-demand rather than continuously. Motion sensors trigger video and audio analysis only when motion is detected, and the system continuously monitors fluid levels at lower power states. This periodic activation maintains high detection precision while significantly reducing energy consumption
Data Source
AI summary
A fuel theft prevention system for a vehicle including: at least one processor; and a memory, operatively connected to the at least one processor and storing instructions that, when executed by the at least one processor, cause the system to: receive, from a first sensing system, first activity data; determine, based on the first activity data, a first confidence value indicative of whether the activity is suspicious; receive fuel data indicative of a fuel level in the fuel tank; and cause, based on the first activity data and the fuel data, at least one mitigation action to be taken when the fuel level decreases by a threshold amount, wherein the threshold amount includes a first amount when the first confidence value is a first value and a second amount when the first confidence value is below the first value, and wherein the second amount is greater than the first amount.