AI Video Classification and Natural Language Search for Building Security
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Solution Overview
Problem
Existing building security systems lack efficient methods for analyzing and searching video data from cameras using artificial intelligence, particularly in responding to specific events or objects and providing relevant search results through natural language inputs.
Innovation Solution
A building security system utilizing an AI model to classify and search video files using an AI model to identify objects and events, applying natural language processing to extract relevant entities from a search query, and presenting results through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video search methods are used, then system complexity is low, but search efficiency and accuracy deteriorate
Solution Approach 1:
The system performs preliminary classification of video files using AI models before search operations. Video files are pre-processed to extract objects, events, and attributes, creating structured metadata that enables rapid searching without complex real-time analysis during query execution.
Solution Approach 2:
The patent introduces an intermediary layer between traditional video search and AI processing. A search manager component translates natural language queries into structured search parameters, mediating between user intent and the complex AI-based video analysis system, thereby simplifying the user interface while maintaining advanced search capabilities.
2Measurement precision
If AI models are applied to classify video files, then search accuracy improves, but processing time increases
Solution Approach 1:
The video processing system is segmented into independent AI models that can process different aspects of video content simultaneously. Multiple object detection models run in parallel to identify different types of objects and events, dividing the processing workload to reduce overall processing time while maintaining high accuracy for each detection task.
Solution Approach 2:
Video files are pre-classified during off-peak times or in the background, creating a structured database of video metadata before search operations are needed. This preliminary processing separates the heavy AI computation from the user interaction timeline, maintaining high detection accuracy while minimizing perceived processing time for end users.
3Ease of operation
If natural language processing is used to extract entities from search queries, then user interface ease of use improves, but processing complexity increases
Solution Approach 1:
A search manager component serves as an intermediary that handles the complexity of natural language processing. This mediator translates diverse natural language queries into standardized search parameters that the video search system can process, shielding users from complexity while enabling sophisticated search capabilities through simple language input.
Solution Approach 2:
The natural language processing system automatically analyzes and structures search queries without requiring user intervention or manual configuration. The system self-adapts to different query formats and languages, automatically extracting relevant entities and parameters while managing its own complexity internally, presenting a simple interface to users.
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.