Automated Video Surveillance Camera Integrity Checks
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Solution Overview
Problem
Existing video surveillance systems require substantial manual resources to perform integrity checks on numerous cameras, which is inefficient and time-consuming, especially as camera performance can degrade due to factors like dust, weather, vandalism, and lighting issues.
Innovation Solution
A method and system that retrieve recent video frames from multiple cameras, calculate integrity scores based on blur, blockage, and exposure, and generate reports to alert users of cameras with scores that fail to meet predetermined criteria, allowing for automated or on-demand checks and enabling manual verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual integrity checks are performed on all cameras, then detection accuracy is improved, but labor resources and time consumption increase substantially
Solution Approach 1:
The patent replaces manual mechanical inspection with automated image processing algorithms. The system uses computer vision techniques to automatically analyze camera images, detect obstructions, and assess integrity, substituting human labor with computational analysis that maintains high detection accuracy while dramatically reducing time consumption.
Solution Approach 2:
The system enables cameras to self-assess their own integrity by automatically analyzing their captured images. Each camera's footage is processed to detect obstructions, focus issues, and other integrity problems without requiring external manual inspection, allowing the surveillance system to monitor itself autonomously.
2Reliability
If manual integrity checks are performed on all cameras, then system reliability is improved, but operational efficiency deteriorates
Solution Approach 1:
The system replaces manual operational processes with automated computational systems. Image processing algorithms continuously analyze camera feeds to assess integrity, replacing the need for security personnel to manually inspect each camera, thereby maintaining system reliability while significantly improving operational efficiency.
Solution Approach 2:
The automated integrity check system operates continuously without interruption, constantly monitoring camera health through ongoing image analysis. This continuous automated operation ensures sustained system reliability while eliminating the downtime and inefficiency associated with periodic manual inspections.
3Productivity
If automated integrity analysis is implemented, then operational efficiency is improved, but system complexity increases
Solution Approach 1:
The system employs universal image processing algorithms that can analyze multiple camera types and detect various integrity issues (obstructions, focus problems, lighting conditions) using the same computational framework. This multi-functional approach improves operational efficiency across diverse camera systems while managing complexity through standardized processing methods.
Data Source
AI summary
A method of performing an integrity check on a plurality of video surveillance cameras includes retrieving a recent video frame from each of the plurality of video surveillance cameras, determining a integrity score for each of the recent video frames and determining which of the integrity scores failed to meet a predetermined criteria. When at least one of the integrity scores fails to meet the predetermined criteria, an integrity check report is created that includes an camera identifier along with the recent video frame for each of the plurality of video surveillance cameras that had a recent video frame with an integrity score that failed to meet the predetermined criteria. The integrity check report is displayed to a user for manual verification.