Mobile App Safety Score Algorithm for Proactive Emergency Response
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Solution Overview
Problem
Current methods for assessing user safety in potentially dangerous situations are manual, stressful, and lack a comprehensive understanding of both current and historical contexts, often failing to initiate proactive responses in emergencies, especially when users are alone and without someone to check in on them.
Innovation Solution
A mobile application that uses passively collected data such as location history, phone usage, and other historical data to compute a safety score, which can proactively alert users and their contacts or authorities if the score falls below a threshold, based on analysis of both current and historical contexts, without requiring additional hardware beyond the user's device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual safety checking methods are used, then users can alert others of danger, but the process is stressful and lacks comprehensive context understanding
Solution Approach 1:
The system enables automatic safety assessment without requiring manual intervention from users or their contacts. The application autonomously collects data, computes safety scores, and initiates alerts, eliminating the stress of manual checking while improving reliability through continuous automated monitoring
Solution Approach 2:
The system continuously monitors user context and provides feedback through safety scores and alerts. By analyzing historical and current data, the system adjusts safety assessments dynamically and notifies appropriate parties when thresholds are breached, creating a reliable closed-loop safety mechanism
2Loss of time
If proactive safety monitoring is implemented, then timely interventions are enabled, but comprehensive analysis of current and historical contexts is required
Solution Approach 1:
The system pre-computes safety scores by continuously analyzing historical context data in the background. When a user is in danger, the pre-analyzed historical patterns enable immediate proactive alerts without requiring complex real-time analysis, thus reducing response time while managing complexity through advance preparation
Solution Approach 2:
The safety assessment system divides complex context analysis into manageable components: historical behavior patterns, current location data, real-time activity context, and threshold comparisons. This segmentation allows the system to process comprehensive data without overwhelming complexity, enabling timely interventions
3Extent of automation
If automated safety scoring is used, then proactive alerts can be sent, but passively collected data from multiple sources must be integrated
Solution Approach 1:
The system uses a unified safety score computation mechanism that universally processes multiple data sources including location history, phone usage patterns, and contextual information. This multi-functional approach integrates diverse data types through a single automated scoring system, reducing the apparent complexity while achieving high automation
Data Source
AI summary
A method for assessing a safety of a user of an application executing on a mobile device, including collecting a location data, a motion data, and a location data source from the application; transmitting, at a time, the location data, the motion data, and the location data source to a server; obtaining, from the server, a normal behavior data associated with the user; determining an abnormality score; determining a confidence score; determining a threat score; determining a threat type; calculating a safety score for the user; determining that the safety score is less than a safety score threshold; and transmitting a message to the mobile device of the user requesting a reply.