Sensor-Based Peril Detection in Assisted Living Environments
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Solution Overview
Problem
Existing systems struggle to effectively detect when individuals in independent or assisted living environments are in peril and provide timely assistance, relying on self-reporting or caregiver notice, which often leads to unaddressed situations.
Innovation Solution
A hardware controller collects and analyzes sensor data from connected devices to identify potentially threatening situations for individuals, generating real-time notifications to appropriate individuals or caregivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data collection and analysis systems are implemented to detect perilous situations, then individual safety and response time are improved, but device complexity and system cost increase
Solution Approach 1:
The system divides the monitoring function into multiple independent sensor components (motion sensors, temperature sensors, humidity sensors, smoke detectors) distributed throughout the living environment. Each sensor independently monitors specific parameters and communicates with a central controller, allowing the system to detect various perilous conditions through modular, segmented sensing rather than requiring a single complex all-encompassing device.
Solution Approach 2:
The controller is designed as a universal device that can process data from multiple types of sensors and implement various response actions (notifications, alarms, automated interventions). This multi-functional controller consolidates what would otherwise require multiple specialized devices, reducing overall system complexity while maintaining comprehensive safety monitoring capabilities.
2Loss of time
If real-time sensor data analysis is performed to detect perilous situations, then response time is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic sampling of sensor data rather than continuous analysis, where the controller checks sensor readings at predetermined time intervals. This periodic action maintains real-time monitoring capability while significantly reducing computational load and energy consumption compared to continuous real-time analysis, as the system only processes data at discrete moments rather than constantly.
Solution Approach 2:
Individual sensors autonomously detect conditions and transmit data to the controller only when threshold violations occur or at periodic intervals, rather than requiring continuous polling by the controller. This self-service approach allows sensors to operate independently and efficiently, reducing the energy burden on the central controller while maintaining timely detection of perilous situations.
Data Source
AI summary
The present embodiments relate to detecting instances of individuals being in peril within an independent or assisted living environment. According to certain aspects, with an individual's permission or affirmative consent, a hardware controller (such as a smart or interconnected home controller, or even a mobile device) may receive and analyze sensor data detected within the independent or assisted living environment to determine whether an individual may be in peril. In this circumstance, the hardware controller may generate a notification that indicates the situation and may communicate the notification to a proper individual, such as a family member or care giver, who may be in a position to mitigate or alleviate any risks posed by the situation. The foregoing functionality also may be used by an insurance provider to generate, update, or adjust insurance policies, premiums, rates, or discounts, and/or make recommendations to an insured individual.