Power Tool Accident Prevention via Visual Hazard Detection
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Solution Overview
Problem
Conventional safety techniques for power tools do not effectively prevent accidents by detecting potential hazards before they occur, relying mainly on flesh proximity detection and failing to address causes like user ineptitude, distraction, fatigue, and improper setup.
Innovation Solution
A system combining visual information from static and wearable cameras with cognitive data from wearables to identify potential accident causes and activate emergency safety measures, such as cutting power to the tool or providing alerts, to prevent accidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional flesh proximity detection is used, then the system can detect immediate dangers, but it cannot prevent accidents before they occur or address root causes like user distraction and fatigue
Solution Approach 1:
The system performs preliminary detection of accident risks by analyzing images from static and wearable cameras to identify dangerous situations before they escalate into actual accidents. The danger identification circuit processes visual data to detect potential hazards such as improper tool operation, unsafe environments, or user distress signals, enabling preventive action before contact with rotating blades occurs.
Solution Approach 2:
The safety system is segmented into multiple independent detection components: static cameras monitoring the environment, wearable cameras on the user, and a centralized danger identification circuit. This segmentation allows each component to specialize in specific detection tasks while maintaining overall system manageability and reducing the complexity burden of comprehensive monitoring.
2Measurement precision
If multiple cameras and cognitive sensors are integrated, then comprehensive accident risk detection is achieved, but system complexity and cost increase
Solution Approach 1:
The wearable camera serves multiple functions: it monitors user facial expressions for distress detection, captures first-person views of tool operation, and provides continuous visual feedback to the danger identification circuit. This multi-functionality reduces the need for separate specialized sensors, thereby improving detection accuracy without proportionally increasing system complexity.
Solution Approach 2:
The danger identification circuit acts as an intermediary that receives and processes data from multiple sources (static cameras, wearable cameras, and cognitive sensors). It consolidates information from these diverse inputs, performs unified analysis, and generates coherent safety decisions, thereby managing the complexity of integrating multiple sensors through a centralized processing layer.
3Reliability
If real-time image analysis is performed to identify inherent dangers, then potential accident causes are detected early, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of images to identify inherent dangers such as improper tool setup, unsafe environmental conditions, or user positioning risks before these develop into immediate threats. By detecting and flagging these potential hazards in advance, the system enables preventive corrections without requiring intensive real-time processing during critical moments.
Solution Approach 2:
The danger identification circuit prioritizes processing by skipping less critical analysis steps when immediate hazards are detected. When the system identifies urgent threats such as user distress or dangerous tool operation, it rushes through the analysis pipeline to provide rapid warnings, thereby reducing processing delay for critical safety events while maintaining thorough analysis for less urgent conditions.
Data Source
AI summary
A power tool accident prevention method, system, and non-transitory computer readable medium receiving images from a static camera of a setup or operation of a power tool, include a danger identification circuit configured to: analyze the images to identify inherent dangers in the setup or the operation of the power tool, and identify at least one potential cause of an accident based on the identified inherent dangers, and a power tool disabling circuit configured to activate an emergency safety measure of the power tool to avoid the at least one potential cause of the accident.