Emergency System for Mobile Users
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Solution Overview
Problem
Conventional technologies do not automatically notify care providers or family members when individuals living alone may need immediate assistance due to being immobile or unable to reach their phones.
Innovation Solution
A comprehensive algorithm is developed to monitor the health and safety of individuals living alone by analyzing their mobile device usage habits and current locations, sending alerts to predetermined contacts when the user is immobile or exceeds established usage thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional emergency applications require the user to manually activate the device or press a button, then the device can be operated when the user is conscious and accessible, but the system fails to detect emergencies when the user is immobile or cannot reach their phone
Solution Approach 1:
The system performs self-monitoring by automatically analyzing the user's mobility and device usage patterns without requiring manual activation. The algorithm detects emergencies autonomously based on deviations from established routines, eliminating the need for the user to press buttons or consciously activate the device during an emergency.
Solution Approach 2:
The system continuously monitors user behavior and provides feedback through automatic emergency detection. By analyzing mobility data and device usage patterns, the system feedbacks whether the user is in distress based on deviations from their normal routine, enabling automatic emergency response without manual input.
2Reliability
If the system continuously monitors user activity and location, then early detection of emergencies is achieved, but energy consumption and system complexity increase
Solution Approach 1:
Instead of continuous monitoring, the system uses periodic analysis of user behavior patterns. It establishes baseline routines during normal periods and periodically compares current activity against these baselines to detect deviations indicating emergencies, thereby reducing energy consumption while maintaining detection reliability.
Solution Approach 2:
The system performs preliminary actions by establishing the user's normal behavior patterns and thresholds during periods when no emergency exists. This preliminary characterization of normal behavior allows the system to later detect anomalies with reduced computational overhead and lower energy consumption during actual monitoring.
3Measurement precision
If the system analyzes detailed usage habits and location data, then accurate emergency detection is achieved, but data processing complexity and computational requirements increase
Solution Approach 1:
The system extracts only the essential features from complex usage data, such as mobility patterns, device usage frequency, and location changes. By focusing on key indicators rather than processing all raw data, the system achieves accurate emergency detection while reducing computational complexity and processing requirements.
Data Source
AI summary
An emergency system and method monitor the health and safety of individuals living alone or in need of assistance on mobile platforms. The emergency system and method detect potential emergencies in advance by analyzing users' mobile device usage habits and the change history of the geolocation of the user's mobile device. A notification is transmitted from the emergency system to the user's mobile device to check on the user based on the usage and the geolocation information. The emergency system and method further detect situations that the user may be in need of immediate assistance, and automatically notify predetermined contacts and/or an official health institution that the user needs immediate attention.