Video Analytics Module for Real-Time Abnormal Situation Detection

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Solution Overview

Problem

Current surveillance systems lack the capability to analyze user behavior in real-time and post-time video streams effectively, particularly in identifying abnormal situations and tracking individuals or objects, which hampers security and investigative efforts.

Innovation Solution

An analytical recognition system comprising video cameras and a video analytics module that performs real-time processing and analysis, using algorithms to identify abnormal situations, track objects or individuals, and store characteristics for future recognition, connected to a network of cameras for comprehensive analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If video buffering is used to store and save video data for later review, then video data can be available for investigative purposes, but the system cannot provide real-time analysis and alerts for abnormal situations

Engineering Contradiction:

Improveresponse time for security eventsVSAvoidreal-time analysis capability

Core Design Contradiction:

Loss of timeVSProductivity

Solution Approach 1:

The system performs preliminary actions by continuously analyzing video streams in real-time to detect abnormal situations before they escalate. The video analytics module proactively identifies potential security threats, crowd anomalies, and suspicious behaviors as they occur, enabling immediate response rather than waiting for buffer review.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces the mechanical approach of manual video review from buffers with automated video analytics using machine learning algorithms. The system substitutes human analysts reviewing stored footage with AI-powered real-time detection that automatically identifies abnormal situations and triggers alerts instantaneously.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If manual review of video buffers is used to identify abnormal situations, then detailed analysis is possible, but the process is time-consuming and cannot keep pace with real-time events

Engineering Contradiction:

Improvedetection accuracy of abnormal situationsVSAvoidtime to detect and respond to events

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The video analytics module performs self-service by autonomously analyzing video streams, detecting abnormal situations, and generating alerts without human intervention. The system serves itself by continuously monitoring multiple camera feeds, applying detection algorithms, and automatically responding to detected anomalies, eliminating the need for manual review while maintaining high detection accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical process of manual video review with automated electronic analysis using machine learning models. The system substitutes human cognitive processing with algorithmic detection that can analyze multiple video streams simultaneously at machine speed, achieving both high precision and real-time performance.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Area of stationary object

If multiple camera systems are deployed to cover large areas, then comprehensive monitoring is achieved, but the complexity of analyzing and correlating video data from multiple sources increases

Engineering Contradiction:

Improvecoverage area of surveillance systemVSAvoidvideo data processing complexity

Core Design Contradiction:

Area of stationary objectVSDevice complexity

Solution Approach 1:

The video analytics module serves multiple functions simultaneously by detecting various types of abnormal situations including crowd anomalies, suspicious objects, loitering behavior, and unusual activities across all camera feeds. The single analytics system handles diverse detection tasks and correlates data from multiple cameras, reducing overall system complexity despite extensive coverage.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent merges the analysis of multiple camera streams into a unified video analytics platform that processes and correlates data from all sources simultaneously. The system combines video feeds, detection algorithms, and alert generation into an integrated solution that manages multi-camera complexity through centralized intelligent processing.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS11587326B2Video identification and analytical recognition system

Publication Date: 2023.02.21 CAREY JAMES

AI summary

An analytical recognition system includes one or more video cameras configured to capture video and a video analytics module configured to perform real-time video processing and analyzation of the captured video and generate non-video data. The video analytic module includes one or more algorithms configured to identify an abnormal situation. Each abnormal situation alerts the video analytics module to automatically issue an alert and track one or more objects or individuals by utilizing the one or more video cameras. The abnormal situation is selected from the group consisting of action of a particular individual, non-action of a particular individual, a temporal event, and an externally generated event.