Wearable PPE Monitoring for Real-Time Hazard-Based Verification
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Solution Overview
Problem
Conventional computer-implemented monitoring systems lack the capability to intelligently assess risks of airborne disease transmission and fail to ensure appropriate personal protective equipment (PPE) is worn correctly in varying environmental conditions, posing a risk to worker safety.
Innovation Solution
A computer-implemented wearable system that integrates with safety equipment and PPE to verify the presence, functionality, and proper wearing of safety gears using wireless communication technologies like Bluetooth, RFID, and NFC, ensuring compliance with environmental hazards through real-time monitoring and alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional monitoring systems are used to track worker safety equipment, then basic presence detection is achieved, but the systems lack capability to intelligently assess airborne disease transmission risks and verify proper PPE wearing
Solution Approach 1:
The patent introduces wearable computing devices and mobile devices as intermediary components that bridge the gap between simple presence detection and intelligent risk assessment. These devices incorporate sensors, processors, and communication modules that enable sophisticated monitoring capabilities while distributing system complexity across multiple components rather than requiring a single complex system
Solution Approach 2:
The monitoring system is designed to perform multiple functions including detecting presence of safety equipment, verifying proper wearing of PPE, assessing airborne disease transmission risks, and providing real-time alerts. This multi-functional approach consolidates what would otherwise require separate systems into a unified platform, improving measurement precision without proportionally increasing overall device complexity
2Reliability
If comprehensive real-time monitoring of safety equipment is implemented, then worker safety is enhanced, but the system requires complex infrastructure and processing capabilities
Solution Approach 1:
The monitoring system is segmented into distinct functional modules: wearable devices worn by workers, mobile devices carried by workers or supervisors, and remote server systems. Each segment handles specific tasks such as local sensor data collection, intermediate processing and alert generation, and centralized data management. This segmentation distributes computational complexity across multiple independent components, enhancing reliability through modular design while avoiding the need for a single complex centralized system
Solution Approach 2:
The wearable devices incorporate onboard processors and decision-making algorithms that enable them to autonomously analyze sensor data and generate alerts without requiring constant connection to external systems. This self-service capability allows the system to maintain high reliability even when communication infrastructure is limited, while reducing the processing burden on centralized systems
3Adaptability or versatility
If intelligent risk assessment capabilities are added to monitoring systems, then airborne disease transmission risks can be detected, but the device complexity and processing requirements increase significantly
Solution Approach 1:
The wearable and mobile devices are designed as universal platforms that can assess multiple types of environmental risks including airborne disease transmission, chemical hazards, and physical dangers. By using the same hardware and software infrastructure for diverse risk assessment functions, the system achieves high adaptability without proportionally increasing processing complexity, as the core computational resources are reused across different monitoring tasks
Data Source
AI summary
A method implemented with an equipment computing device associated with safety equipment. The step includes determining that the equipment computing device is in an environment that requires safety equipment to be worn. The method determines environmental data based on the determination that the equipment computing device is in the environment. The method then determines operation metrics of the environment based on the environmental data and then determines a list of predetermined safety gears along with safety-related data that are applicable for the operation metrics. A set of identification indicators including real-time operative information is acquired from each of one or more safety gears of the safety equipment. The method then detects and indicates that the one or more safety gears along with one or more operative measures are present in the safety equipment for operating according to the determined operation metrics of the environment by comparing the acquired set of identification indicators including the real-time operative information of each of the one or more safety gears with each of the predetermined safety gears and the safety-related data of each of the predetermined safety gears. The method assigns one of the one or more safety gears as a primary gear to verify each of the one or more safety gears, the primary gear is communicating with each of the one or more safety gears through any of Bluetooth, Bluetooth mesh, Radio Frequency Identification (RFID), Zigbee, Wireless Body Area Network (WBAN) and Near Field Technology (NFC) for acquiring the identification indicators including the real-time operative information from each of the one or more safety gears.