Video Event Notification System Using Segmented Analysis
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Solution Overview
Problem
Current video analytics technologies are limited in their ability to characterize video content effectively, requiring significant processing capacity and dedicated networks, making them impractical for real-time analysis and distribution across standard networks, and lacking flexibility to adapt to dynamic situations or user preferences.
Innovation Solution
A novel method and system for remote event notification and personalized video content delivery, which involves analyzing video data in real-time, selecting segments of interest based on user-defined preferences, and sending notifications or video streams over existing networks, including the Internet and wireless infrastructure, allowing for flexible recipient specification and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video analytics technology is used to analyze video data in real-time, then the ability to detect and characterize video content is improved, but the processing capacity requirements increase significantly
Solution Approach 1:
The system segments video content analysis into multiple components: motion detection identifies regions of interest, object recognition classifies specific objects, and event detection identifies significant occurrences. This segmentation allows distributed processing across multiple devices and reduces the processing burden on any single device, enabling real-time analysis without requiring excessive processing capacity at one location.
Solution Approach 2:
The system performs preliminary video compression and encoding before transmission over networks. By pre-processing video data to reduce its size and format it for efficient transmission, the system reduces the processing and bandwidth requirements for subsequent analysis and distribution, enabling deployment on standard networks rather than requiring dedicated high-bandwidth infrastructure.
2Reliability
If existing video systems are deployed on dedicated networks, then video transmission reliability is improved, but the system flexibility and adaptability to dynamic situations deteriorates
Solution Approach 1:
The system is designed to operate on standard, widely-available networks (Internet, wireless networks, Ethernet) rather than requiring dedicated video transmission infrastructure. By making the system compatible with universal network protocols and formats, it gains flexibility to be deployed in diverse environments and adapted to dynamic situations while maintaining reliable video transmission through proven network infrastructure.
Solution Approach 2:
The system dynamically adapts its operation based on network conditions, user preferences, and detected events. It can adjust video quality, transmission frequency, and notification methods in real-time, allowing it to maintain reliable performance across varying network conditions while remaining flexible enough to respond to changing requirements and situations.
3Ease of operation
If users actively pull video streams to view content, then video delivery control is improved, but user convenience and time efficiency deteriorates
Solution Approach 1:
The system incorporates event detection and automatic notification mechanisms that provide feedback to users about significant occurrences. When the system detects a predefined event (such as motion, object presence, or specific conditions), it automatically generates and sends notifications to users, eliminating the need for users to continuously monitor or manually search for content of interest.
Solution Approach 2:
The system performs automatic event detection, video segment selection, and notification delivery without requiring user intervention. Users configure their preferences once, and the system autonomously monitors video feeds, identifies significant events, selects relevant video segments, and delivers them to users, saving considerable time and effort compared to manual content browsing.
4Productivity
If video motion detection is used to trigger video transmission, then the ability to initiate video delivery is improved, but the ability to determine content relevance deteriorates
Solution Approach 1:
The system replaces simple motion detection mechanisms with advanced video analytics technology that uses computer vision, object recognition, and event detection algorithms. This substitution enables the system to not only detect motion but also understand and classify the content being detected, determining whether the motion represents a significant event worthy of user notification based on predefined criteria and user preferences.
Data Source
AI summary
A method for remote event notification over a data network is disclosed. The method includes receiving video data from any source, analyzing the video data with reference to a profile to select a segment of interest associated with an event of significance, encoding the segment of interest, and sending to a user a representation of the segment of interest for display at a user display device. A further method for sharing video data based on content according to a user-defined profile over a data network is disclosed. The method includes receiving the video data, analyzing the video data for relevant content according to the profile, consulting a profile to determine a treatment of the relevant content, and sending data representative of the relevant content according to the treatment.