Vehicle Perimeter Surveillance With AI False Alarm Filtering
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Solution Overview
Problem
Existing vehicle security systems are passive, often triggering false alarms due to weather conditions, loud noises, or accidental tripping, and lack adaptability and a comprehensive view of the surroundings.
Innovation Solution
A self-powered, adaptive perimeter security system for vehicles that utilizes multiple sensors and cameras strategically placed in a unique enclosure design, processing environmental data with AI and ML to detect potential threats and differentiate between true and false alarms, and notifying the vehicle's owner through a mobile phone application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors and cameras are used to improve security detection accuracy, then the ability to distinguish true threats from false alarms is improved, but the device complexity and cost increase
Solution Approach 1:
The system divides the security monitoring function into multiple specialized sensors (motion sensors, sound detectors, light sensors, cameras) strategically placed at different locations. Each sensor type detects specific aspects of potential threats, and their data is processed separately before being integrated by the AI/ML processor to achieve accurate threat identification while managing complexity through functional segmentation.
Solution Approach 2:
The AI and ML processors serve multiple functions: they analyze data from all sensor types, distinguish between true threats and false alarms, control the alarm system, and manage communication with mobile devices. This multi-functionality reduces the need for separate dedicated components for each task, thereby managing overall system complexity while maintaining high detection accuracy.
2Device complexity
If sensors are placed internally within the vehicle, then the device complexity is reduced and installation is simplified, but the view of surrounding area is obstructed and detection capability is limited
Solution Approach 1:
The system transitions from internal placement to external rooftop mounting, utilizing the vertical dimension and elevated position to achieve an unobstructed 360-degree view of the surrounding area. This dimensional change allows sensors and cameras to detect threats from all directions without being blocked by vehicle structures, significantly improving detection capability while maintaining manageable design complexity through a centralized enclosure.
3Ease of operation
If passive alarm systems are used to reduce system complexity, then the system is easier to operate, but false alarms are frequent and reliability is reduced
Solution Approach 1:
The AI and ML processors continuously analyze sensor data in real-time, providing feedback to determine whether detected anomalies represent true threats or false alarms. The system learns from patterns in the data and adjusts its response accordingly, maintaining simple operation for the user while significantly improving alarm accuracy and reliability by filtering out false positives through intelligent analysis.
Data Source
AI summary
An embodiment designed to be attached to a vehicle comprising of multiple sensors and AI/ML cameras that provide round the clock perimeter surveillance for said vehicle. The embodiment utilizes data from the sensors and cameras to identify potential threats, accidents or an occurrence of damage to the vehicle. The device provides communication of processed events and provides notifications to end-user (vehicle owner) utilizing wireless communications. The embodiment itself is self-powered utilizing solar power to keep an internal battery pack charged for day and night operation of the entire electronic system.