Safety Event Prediction via Multi-Sensor Fusion
Solution Overview
Problem
Traditional alert devices fail to provide sufficient details on a user's current status, often send false alarms, miss identifying actual safety events, and do not anticipate or prevent such events from occurring, due to limitations in sensor accuracy and integration of data from movement, physiological, and environmental sensors.
Innovation Solution
An electronic device equipped with an integrated sensor array that includes movement, physiological, and environmental sensors, processing logic to analyze measurement information, and send alerts when safety events are identified or predicted, providing accurate and timely notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional alert devices use simple sensors and basic algorithms, then device complexity is reduced, but measurement precision and reliability deteriorate due to insufficient sensor accuracy and data integration capabilities
Solution Approach 1:
The patent combines multiple sensor types (movement sensors, physiological sensors, environmental sensors, location sensors) into an integrated sensor array within a single electronic device. This merging of sensors allows comprehensive data collection while maintaining device portability and usability, resolving the contradiction between simplicity and measurement precision.
Solution Approach 2:
The electronic device is designed to perform multiple functions: monitoring movement, physiological status, environmental conditions, and location simultaneously. This multi-functional approach enables the device to provide comprehensive safety monitoring without requiring multiple separate devices, thereby maintaining ease of use while improving measurement precision through integrated sensing.
2Reliability
If traditional alert devices use simple monitoring algorithms, then processing speed and energy consumption are reduced, but reliability deteriorates due to false alarms and missed safety events
Solution Approach 1:
The system performs preliminary analysis of sensor data locally using processing logic to identify potential safety events before they occur. By anticipating safety events through pattern recognition and predictive algorithms, the system can alert users in advance, improving reliability while optimizing energy consumption by processing data efficiently rather than continuously transmitting all raw data.
Solution Approach 2:
The device incorporates feedback mechanisms where processing logic continuously analyzes data from multiple sensors and adjusts monitoring parameters based on detected patterns. This feedback loop improves reliability by reducing false alarms through learned patterns while managing energy consumption by intensifying monitoring only when necessary based on detected anomalies.
3Reliability
If continuous supervision by caregivers is implemented, then safety monitoring is improved, but economic feasibility deteriorates due to high costs
Solution Approach 1:
The electronic device enables self-service safety monitoring where individuals monitor their own status autonomously without requiring continuous human supervision. The device automatically collects data from sensors, analyzes it through processing logic, and generates alerts when safety events are detected, making reliable safety monitoring economically feasible by replacing costly continuous caregiver supervision with an autonomous system.
4Loss of information
If traditional alert devices provide basic alerts, then device complexity is reduced, but loss of information occurs due to insufficient details on user status
Solution Approach 1:
The system transitions from providing single-dimension basic alerts to multi-dimensional comprehensive status reporting by integrating data from multiple sensor types (movement, physiological, environmental, location). This dimensional expansion of information provides detailed user status context without requiring proportionally complex device architecture, as the complexity is managed through integrated processing logic that synthesizes data from the sensor array.
Data Source
AI summary
A method, system, device, or apparatus for notifying a device of a greater number of safety events associated with the first user. The method includes retrieving safety events associated with a first user of a first electronic device and determining a frequency of safety events. The method includes retrieving safety events associated with a second user of a second electronic device and determining a frequency of safety events. The method includes comparing the frequency of safety events associated with the first user and the number of safety events associated with the second user and determining that there is a greater frequency of safety events associated with the first user than with the second user for the period of time. The method includes determining a cause of the greater frequency of safety events associated with the first user.