Cascade Deep Learning Safety Management for Industrial Monitoring
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Solution Overview
Problem
Conventional safety management systems in industrial sites require multiple sensors for various functions, which are difficult to install and costly to maintain, especially in environments where sensor installation is challenging, and there is a need for a technology that can perform safety management using camera-based image analysis without additional hardware.
Innovation Solution
A system utilizing a cascade deep learning network that includes a camera module and a processor to analyze real-time image data, applying object recognition, posture estimation, and motion classification models to detect potential hazards and control responses, such as stopping facilities or robots, without the need for additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are installed for various safety functions, then detection accuracy is improved, but device complexity and installation difficulty increase
Solution Approach 1:
The patent applies multi-functionality by enabling a single camera system to perform multiple safety detection functions including worker detection, fire detection, smoke detection, and motion analysis. The cascade deep learning network integrates multiple detection capabilities within one system, eliminating the need for separate sensors for each function while maintaining comprehensive safety monitoring
Solution Approach 2:
The patent merges multiple detection functions into a unified camera-based system. The cascade deep learning network combines object detection, fire detection, smoke detection, and motion classification models into a single integrated framework that processes camera images to achieve comprehensive safety monitoring with one device
2Measurement precision
If multiple sensors are installed for various safety functions, then detection accuracy is improved, but installation and maintenance costs increase
Solution Approach 1:
The patent reduces installation and maintenance costs by deploying a single camera system that performs multiple safety functions. The cascade deep learning network provides fire detection, smoke detection, worker detection, and motion analysis capabilities within one system, eliminating the need to purchase, install, and maintain multiple separate sensors
Solution Approach 2:
The patent uses image data captured by the camera as a virtual copy of the physical environment, allowing the system to detect hazards and analyze worker behavior through digital processing of visual information rather than requiring physical sensors throughout the workspace
3Reliability
If sensors are installed in specific areas, then detection reliability is improved, but adaptability to different site configurations decreases
Solution Approach 1:
The patent applies dynamics by implementing a mobile robot platform that can move to different locations and adjust its monitoring coverage dynamically. The system adapts to different site configurations by repositioning the camera and adjusting detection parameters based on the current environment, maintaining reliable detection across varying spatial arrangements
Solution Approach 2:
The patent enhances adaptability by designing a universal camera-based detection system that can operate in various industrial site configurations. The cascade deep learning network processes images to detect multiple hazard types and worker behaviors, allowing the system to adapt to different layouts and environments without requiring site-specific sensor installations
4Adaptability or versatility
If a robot moves in the area, then monitoring flexibility is improved, but sensor application becomes difficult
Solution Approach 1:
The patent applies self-service by equipping the mobile robot with autonomous navigation and self-monitoring capabilities. The robot independently moves through the workspace, captures images with its onboard camera, and processes the data using the cascade deep learning network to detect hazards and worker behaviors without requiring external sensor infrastructure
Solution Approach 2:
The patent resolves the sensor application difficulty by using a universal camera-based detection system mounted on the mobile robot. The single camera performs multiple detection functions including fire, smoke, worker presence, and motion analysis, eliminating the need for multiple specialized sensors that would be difficult to install in a mobile platform
Data Source
AI summary
The present disclosure relates to a system for safety management based on a cascade deep learning network, and the system for safety management based on the cascade deep learning network includes a camera module that captures image of an area to be monitored at an industrial site; and a processor that receives and analyzes image data captured by the camera module in real time.