AI Video Classification for Natural Language Security Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing building security systems lack efficient methods for analyzing and searching video data from cameras using artificial intelligence, particularly in classifying and retrieving relevant video files based on natural language search queries, which hinders effective monitoring and response to security events.
Innovation Solution
Implementing an AI model, such as a foundation AI model or a large language model, to classify video files, extract entities from natural language search queries, and search video files using natural language processing, with capabilities for real-time analysis and automated actions based on detected objects or events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video search methods are used, then system complexity remains low, but video data retrieval efficiency is poor
Solution Approach 1:
The system performs preliminary classification of video files by detecting objects, people, and events before search operations. AI models analyze video content in advance and generate metadata tags, enabling rapid retrieval without complex real-time analysis during search operations.
Solution Approach 2:
The patent introduces an intermediary layer of AI-generated metadata between the video files and search queries. Natural language processing converts user queries into structured search parameters that match against pre-generated video metadata, simplifying the search mechanism while improving efficiency.
2Reliability
If AI models are deployed for real-time video analysis, then security monitoring capability is enhanced, but processing time increases
Solution Approach 1:
The system segments video analysis into distinct processing stages: object detection, event recognition, and metadata generation. Each stage processes specific aspects of video content independently, allowing parallel processing and reducing overall analysis time while maintaining comprehensive security monitoring.
Solution Approach 2:
The AI models focus on detecting only the most relevant security-critical objects and events rather than analyzing every detail of video content. This selective approach maintains high security monitoring capability while significantly reducing processing time and computational resources required.
3Measurement precision
If comprehensive video classification is applied, then search accuracy is improved, but computational resources consumed increase
Solution Approach 1:
The system applies different levels of classification detail to different video segments based on their security relevance. High-priority areas receive comprehensive AI analysis with detailed metadata, while low-priority areas receive basic classification, optimizing the balance between search accuracy and computational resource consumption.
Data Source
AI summary
A building security system is configured to apply classifications to video files using an artificial intelligence (AI) model. The classifications include one or more objects or events recognized in the video files by the AI model. The system is configured to extract one or more entities from a search query received via a user interface. The entities include one or more objects or events indicated by the search query. The system is configured to search the video files using the classifications applied by the AI model and the one or more entities extracted from the search query and present one or more of the video files identified as results of the search query as playable videos via the user interface.