Anomaly Notification System Using Activity Amount Verification
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Solution Overview
Problem
Conventional anomaly notification systems in care settings often generate false alarms due to non-relevant sounds, failing to appropriately notify caregivers of actual anomalies in cared persons, such as falls or breathing troubles, as they rely solely on sound volume without distinguishing between relevant and irrelevant sounds or activity-related noises.
Innovation Solution
An anomaly notification system that includes sensors to measure activity levels, a sound collection unit to differentiate between sound volumes, and determination units to identify specific activity sounds and assess changes in activity levels before and after sound generation, ensuring accurate anomaly detection and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If sound volume threshold is used for anomaly detection, then anomaly notification speed is improved, but false alarm rate increases
Solution Approach 1:
The sound detection process is segmented into multiple stages: initial sound volume detection, activity sound type identification, and activity amount change verification. This multi-stage segmentation allows the system to quickly respond to potential anomalies while systematically filtering out false alarms through progressive verification steps.
Solution Approach 2:
Activity sound type identification serves as an intermediary verification step between sound volume detection and final anomaly notification. The determination unit acts as a mediator that checks whether the sound matches expected activity patterns before triggering an alarm, thereby reducing false notifications while maintaining rapid response capability.
2Reliability
If multiple determination steps are added to reduce false alarms, then notification accuracy is improved, but system complexity increases
Solution Approach 1:
The determination unit performs multiple functions within a single component: it identifies activity sound types, compares sounds against reference patterns, and evaluates activity amount changes. This multi-functionality reduces the need for separate dedicated components for each determination step, thereby limiting the increase in system complexity while maintaining high notification accuracy.
Solution Approach 2:
The system stores reference activity sound types and activity amount thresholds in advance before actual anomaly detection occurs. This preliminary preparation allows the determination unit to perform rapid comparisons during operation without requiring complex real-time analysis, thus improving accuracy while keeping the operational system relatively simple.
3Measurement precision
If activity amount monitoring is added to sound detection, then detection precision is improved, but device complexity increases
Solution Approach 1:
The system merges sound detection functionality with activity amount monitoring into an integrated anomaly detection framework. The determination unit combines information from both sound volume/Type and activity amount sensors to make comprehensive anomaly assessments, thereby improving detection precision while avoiding the complexity of completely separate detection systems.
Solution Approach 2:
The system monitors changes in activity amount parameters before and after sound events rather than requiring continuous detailed tracking of all activity parameters. By focusing on parameter changes (delta values) rather than absolute continuous monitoring, the system achieves improved detection precision with minimal additional device complexity.
Data Source
AI summary
Anomaly notification system that notifies of an anomaly of cared person in room includes sensor, sound collecting unit, first determination unit that determines whether a volume of the collected sound is more than or equal to a reference volume, second determination unit that determines whether a target sound is a predetermined activity sound generated by an activity of cared person, and third determination unit that determines whether an anomaly occurs in cared person, based on the activity amounts, which are measured before and after the target sound is collected, and notification unit.