AI Camera Verification System for Surveillance Reliability
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Solution Overview
Problem
Surveillance systems face challenges due to camera malfunctions, physical or digital attacks, and the inefficiency of manual verification processes, especially in large-scale environments with diverse camera and recorder manufacturers, leading to potential missed incidents and high operational costs.
Innovation Solution
An automated camera operation verification system utilizing AI models to detect issues such as scene changes, blocked views, and cyber-attacks, which performs real-time inspections and corrective actions without requiring specific hardware, ensuring continuous surveillance across various conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual verification of each camera is performed to ensure proper recording, then reliability of surveillance is improved, but productivity and ease of operation deteriorate due to the slow and tedious process
Solution Approach 1:
The system enables self-verification where the surveillance system automatically checks its own operation status, camera functionality, and recording integrity without requiring manual intervention. The AI model analyzes video feeds and system parameters to detect issues such as blocked views, camera movement, and recording failures, allowing the system to monitor and verify itself autonomously.
Solution Approach 2:
The patent replaces manual mechanical verification processes with an automated AI-based system. Instead of operators physically checking each camera, the system uses machine learning models to analyze video data, detect anomalies, and verify operational status automatically, substituting human labor with intelligent automation.
2Reliability
If manual verification of each camera is performed to ensure proper recording, then reliability of surveillance is improved, but loss of time increases due to the tedious process
Solution Approach 1:
The system performs continuous verification of camera operations and recording status without interruption. The AI model continuously monitors video feeds, system parameters, and recording integrity, ensuring that verification is an ongoing process rather than periodic manual checks, thereby eliminating verification time loss while maintaining constant reliability.
Solution Approach 2:
The surveillance system automatically performs its own verification operations continuously, eliminating the need for operators to allocate time for manual checks. The system self-monitors its health, camera status, and recording functionality, ensuring verification occurs without time loss.
3Reliability
If manual verification is performed across multiple manufacturers' equipment, then reliability is improved, but device complexity increases due to diverse camera and recorder systems
Solution Approach 1:
The AI verification system is designed as a universal platform that can interface with and verify multiple manufacturers' cameras and recorders through standardized protocols and adaptive learning. The system performs multiple verification functions including camera status monitoring, recording integrity checking, and anomaly detection across heterogeneous equipment without requiring manufacturer-specific complex integration.
4Reliability
If operators view each camera to verify recording, then reliability is improved, but ease of operation deteriorates due to the cumbersome process
Solution Approach 1:
The system automatically performs verification operations without requiring operator intervention. The AI model independently analyzes camera status, video quality, and recording integrity, making the verification process as convenient as having a dashboard display system health status without requiring operators to manually check each camera.
Solution Approach 2:
The system provides continuous feedback to operators about camera and recording status through visual indicators, alerts, and reports. This feedback mechanism eliminates the need for operators to manually verify each camera while maintaining awareness of system reliability, making operation much more convenient.
Data Source
AI summary
A video camera recording system is provided. The aspects include one or more memories configured to store program code. The program code is for performing an automated verification test of elements of the video camera recording system using at least one artificial intelligence (AI) model to identify potential issues with the elements of the video camera recording system. The aspects further include one or more processors, operatively coupled to the one or more memories and configured to run the program code. The aspects also include a transceiver configured to transmit instructions causing a corrective action to be performed for at least one of the potential issues.