Personal Safety Monitoring Using Multi-Sensor Risk Prediction
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Solution Overview
Problem
Existing personal safety devices face limitations in user interaction requirements, detection versatility, and reliability, and often require separate devices rather than integration with personal items like smartphones or smartwatches.
Innovation Solution
A method and device that utilize sensor data, including visual and voice patterns, heart rate, and blood pressure measurements, combined with contextual data and machine learning algorithms, to predict safety risks and take actionable responses, such as alerts or deterrents, through integrated devices like smartphones or smartwatches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing personal safety devices rely on user interaction for detecting safety situations, then the device can be simple and cost-effective, but the detection capability is limited and may not activate during high-stress situations
Solution Approach 1:
The system performs automatic safety monitoring without requiring user interaction. The processing unit autonomously collects sensor data, executes safety risk prediction algorithms, and triggers appropriate responses based on detected risks, eliminating the need for user input during critical situations.
Solution Approach 2:
The patent replaces manual user interaction with automated electronic sensing and processing. Multiple sensors (imaging, sound, heart rate, blood pressure) automatically detect physiological and environmental indicators of safety risks, substituting the mechanical action of user button-pressing or activation with automated electronic monitoring.
2Adaptability or versatility
If existing safety devices have automated detection capability, then user interaction is not required, but the detection versatility and reliability are limited
Solution Approach 1:
The system integrates multiple sensor types (imaging sensor for visual detection, sound sensor for voice pattern analysis, heart rate sensor for physiological monitoring, blood pressure sensor for health status) into a single unified safety device. This multi-functional approach enables the device to detect various types of safety risks through different sensing modalities, significantly enhancing detection versatility.
Solution Approach 2:
The patent combines diverse sensor data streams (visual, auditory, physiological measurements) and processes them through a composite safety risk prediction algorithm. This integration of multiple data sources and processing approaches creates a robust, reliable detection system that can identify safety risks through various patterns and indicators.
3Reliability
If a dedicated personal safety device is carried, then the device can be optimized for safety functions, but the device adds to the number of items to carry and may not be integrated with existing personal devices
Solution Approach 1:
The patent merges safety monitoring functionality with existing personal devices such as smartphones and smartwatches. The processing unit executes safety risk prediction algorithms using sensors already present in these devices, combining safety functions with daily-used technology to eliminate the need for separate dedicated safety devices.
Solution Approach 2:
The system leverages the multi-functional capabilities of existing devices (smartphones, smartwatches) to perform safety monitoring. These devices already contain cameras, microphones, heart rate sensors, and processing units that can be utilized for safety risk detection, making the safety function an additional capability rather than a separate device.
4Adaptability or versatility
If multiple sensors and processing algorithms are integrated into the device, then detection versatility and reliability improve, but the device complexity increases
Solution Approach 1:
The system divides the safety monitoring function into separate modular components: individual sensors (imaging, sound, heart rate, blood pressure) that can be independently activated, and distinct processing stages (data collection, risk prediction, response triggering). This segmentation allows the system to manage complexity through modular architecture while maintaining high detection capability.
Solution Approach 2:
The patent implements selective sensor activation based on detected conditions. Not all sensors operate simultaneously; instead, the system activates appropriate sensors and processing algorithms based on the specific safety risk indicators detected, reducing overall system complexity while maintaining comprehensive detection capability when needed.
Data Source
AI summary
The present specification provides a method for implementing personal safety functionalities. The method comprises collecting sensor data from at least one sensor of a device and executing by a processing unit of the device a safety risk prediction algorithm. The algorithm uses inputs comprising the sensor data to determine a safety risk indicator where the safety risk indicator is indicative of whether a user of the device is exposed to a safety risk presented by at least one person in the vicinity of the user of the device. The method further takes at least one action by the processing unit of the device when the indicator indicates that the user is exposed to a safety risk. The present also provides a safety device, and instructions to be executed by a processing unit.