Hazard Risk Score Calculation for Proactive Injury Prevention
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Solution Overview
Problem
Incidents such as falls and collisions in public locations, leading to traumatic brain injuries and other injuries, are not effectively tracked or correlated to locations, leaving vulnerable individuals without warning of potential hazards.
Innovation Solution
A system utilizing computing devices to detect individual presence and calculate a hazard risk score based on data from the individual and location, incorporating gait analysis, geo-location, and environmental factors, to provide notifications for proactive measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If incidents are tracked and correlated to locations, then hazard risk management is improved, but system complexity and data infrastructure requirements increase
Solution Approach 1:
The patent introduces a server as an intermediary component that receives incident data from multiple computing devices, processes the data to generate hazard risk scores, and distributes notifications. This intermediary architecture allows the system to track and correlate incidents across locations without requiring direct complex interactions between all devices, thereby improving reliability while managing system complexity through centralized coordination.
Solution Approach 2:
The computing devices in the system serve multiple functions: they detect individual presence, collect incident data, provide location information, receive hazard risk scores, and display notifications. This multi-functionality reduces the need for separate specialized devices for each task, improving hazard risk management capability while minimizing the increase in overall system complexity.
2Object-affected harmful factors
If hazard risk scores are calculated and notifications provided, then injury prevention is improved, but data processing requirements and computational resources increase
Solution Approach 1:
The system calculates hazard risk scores in advance based on historical incident data and location information before incidents occur. By performing this data processing and risk assessment preliminarily, the system prepares hazard risk information ready for notification, reducing the need for intensive real-time computational resources when actual incidents occur and improving injury prevention effectiveness.
Solution Approach 2:
Computing devices utilize their own sensors and onboard processors to detect individual presence, collect local incident data, and display notifications. This self-service capability reduces the computational burden on centralized servers, allowing the system to provide hazard risk notifications while minimizing overall data processing requirements and energy consumption.
3Measurement precision
If location and incident data are collected from multiple sources, then hazard risk accuracy is improved, but data privacy and security concerns increase
Solution Approach 1:
The system extracts and processes only the specific incident data and location information necessary for calculating hazard risk scores, rather than collecting and storing all possible personal data. By selectively extracting only the essential information needed for risk assessment, the system improves hazard risk accuracy while minimizing data privacy concerns by not retaining unnecessary personal information.
Data Source
AI summary
Embodiments for managing hazard risk by one or more processors are described. A presence of an individual at a location is detected. A hazard risk score is calculated based on at least one data source associated with at least one of the individual and the location. A notification of the calculated hazard risk score is caused to be generated.