Computer Vision Zone Violation Detection for Workplace Hazards
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual monitoring for safety hazards in work environments is laborious, time-consuming, and subjective, often failing to identify potential hazards before accidents occur, leading to inefficiencies and liability concerns.
Innovation Solution
An automated safety monitoring system using computer vision techniques, including deep-learning models, to detect objects and determine their spatial positions within predefined zones, generating reports on violations and enabling faster remediation of safety hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring is used to detect safety hazards, then inspectors can identify dangerous conditions, but the process is laborious, time-consuming, and subjective
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated computer vision system using cameras and image processing algorithms. The system captures images of the work environment, automatically detects objects and their positions, determines zone violations, and generates reports without human intervention, thereby eliminating the time-consuming and subjective nature of manual monitoring while maintaining or improving detection accuracy.
2Reliability
If manual inspection is performed to ensure safety standards, then hazards can be identified, but the process lacks standardization and consistency
Solution Approach 1:
The patent replaces variable human judgment with a standardized automated system. The computer vision system applies consistent algorithms and criteria to all inspections, ensuring uniform detection standards across different times and inspectors. The system processes images through defined logical operations to determine zone violations, eliminating subjectivity and improving consistency while the complexity is managed through software automation.
3Productivity
If automated computer vision system is implemented, then monitoring efficiency and standardization improve, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional computer vision system that performs multiple tasks: capturing images, detecting objects, determining positions, identifying zone violations, and generating reports. By consolidating these functions into a single automated system, the patent achieves high monitoring efficiency and standardization while managing complexity through integrated design rather than separate manual processes.
Data Source
AI summary
Devices and techniques are generally described for computer vision techniques for safety hazard detection. A frame of image data representing a physical environment is received. In some examples, a first object represented in the frame of image data may be detected. A determination may be made that the first object is of a first class. A first zone represented in the frame of image data may be identified. The first zone may correspond to a ground surface of the physical environment. A determination may be made that the first object at least partially overlaps with the first zone. A first rule associated with the first zone may be determined. The first rule may restrict objects of the first class from being present within the first zone. Output data may be generated indicating that the first object is at least partially within the first zone, in violation of the first rule.