Sensor Classifier Monitoring for Moisture-Driven Appliance Replacement
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Solution Overview
Problem
Existing personal care systems, such as ostomy and wound dressing systems, lack efficient and reliable methods for monitoring moisture propagation and operating states, leading to potential leakage and skin damage without timely replacement.
Innovation Solution
A personal care system with a monitor device and sensor classifier that optimizes data transfer and sensor state determination, using a standardized interface to facilitate reliable monitoring of moisture propagation and operating states, enabling timely replacement and maintaining optimal conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous monitoring of sensor data is implemented, then reliability of moisture propagation detection is improved, but power consumption increases
Solution Approach 1:
The monitor device transitions from continuous monitoring to periodic sampling of sensor data at predetermined intervals. This allows the system to maintain reliability through regular updates while significantly reducing power consumption by keeping the processor in low-power states between sampling intervals.
Solution Approach 2:
The system implements self-service through automated sensor state classification and monitoring functions. The processor automatically analyzes sensor data, classifies sensor states, and determines moisture propagation without requiring external intervention, optimizing the balance between monitoring reliability and power efficiency.
2Adaptability or versatility
If multiple sensor types with different data formats are supported, then adaptability of the system is improved, but device complexity increases
Solution Approach 1:
The monitor device implements a universal data handling framework that can accommodate multiple sensor types (capacitive, resistive, conductive) with different data formats through a single standardized interface. The system classifies sensor states into common categories (normal, warning, critical) regardless of the underlying sensor technology, reducing overall system complexity.
Solution Approach 2:
The system introduces a sensor state classification layer that acts as an intermediary between raw sensor data and higher-level processing. This intermediate layer translates diverse sensor outputs into unified state representations, simplifying data handling while maintaining adaptability to different sensor types.
3Speed
If real-time data processing is performed, then responsiveness to moisture propagation is improved, but computational load increases
Solution Approach 1:
The system performs partial data processing by focusing computational resources on analyzing only the most critical sensor parameters and state transitions. Rather than processing every raw data point, the system samples at key intervals and processes only the essential information needed to detect moisture propagation, reducing computational load while maintaining responsiveness.
Solution Approach 2:
The system replaces complex real-time computational analysis with simpler threshold-based detection and state classification mechanisms. By using predetermined thresholds and categorical state representations, the system achieves responsive moisture propagation detection with significantly reduced computational complexity.
Data Source
AI summary
Monitor device of a personal care system, devices of a personal care system and related methods are disclosed. The monitor device comprises a processor; a memory connected to the processor; a first interface connected to the processor, the first interface configured for connecting the monitor device to the personal care appliance; and a second interface comprising a transceiver module connected to the processor and configured for connecting the monitor device to the accessory device of the personal care system, wherein the monitor device is configured to obtain first sensor data from a first sensor of the personal care appliance; obtain second sensor data from a second sensor of the personal care appliance; determine a first sensor state of the first sensor based on the first sensor data; determine a second sensor state of the second sensor based on the second sensor data; and output a first sensor state identifier indicative of the first sensor state and a second sensor state identifier indicative of the second sensor state.