Camera-Based Event Recognition for Real-Time Equipment Control
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Solution Overview
Problem
Existing systems lack an efficient method to recognize events involving equipment objects in real-time using camera systems, leading to inadequate control and monitoring of these objects in various environments.
Innovation Solution
An event recognition system comprising a camera and a controller that captures image data, processes it to recognize events, and executes procedures such as controlling equipment objects, transmitting data to network-based clients, and managing image data communication through a messaging hub and video frame transmission service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time event recognition is implemented using camera systems, then operational efficiency and safety are improved, but device complexity and processing requirements increase
Solution Approach 1:
The system segments the complex event recognition task into multiple independent modules: image capture module, image processing module, event recognition module, and control module. Each module handles a specific function, allowing parallel processing and reducing overall system complexity while maintaining real-time capabilities.
Solution Approach 2:
An intermediary processing layer is introduced between the camera system and the control system. This intermediary includes image preprocessing and feature extraction components that simplify the data before passing it to the event recognition algorithm, reducing computational burden while maintaining recognition accuracy.
2Measurement precision
If comprehensive image data processing is performed to accurately recognize events, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing images and extracting key features before the actual event recognition occurs. Image enhancement, noise filtering, and feature detection are executed in advance, so when an event needs to be recognized, the processing is already optimized and faster.
Solution Approach 2:
The system applies partial processing to routine scenarios and excessive (comprehensive) processing only when necessary. For normal operations, simplified recognition algorithms are used, while for critical or ambiguous events, full comprehensive analysis is performed, optimizing the balance between accuracy and speed.
3Reliability
If multiple camera systems are integrated for comprehensive monitoring, then reliability is improved, but device complexity increases
Solution Approach 1:
Multiple camera systems are merged into a unified monitoring framework with centralized control. The system combines images from multiple cameras, synchronizes timing, and integrates detection results, achieving comprehensive monitoring coverage while managing complexity through unified architecture and shared processing resources.
Data Source
AI summary
Event recognition systems include a camera and a controller. The controller is communicatively connectable to the camera, and includes a processor and logic that, when executed by the processor, causes the event recognition system to perform operations including: recognizing an event involving an equipment object based upon image data captured by the camera, executing an event procedure based upon the event, the event procedure including controlling the equipment object, and transmitting the image data to a network-based client based upon the event.