ArticleSensors (Basel, Switzerland)2025
Noninvasive Acoustic Recognition of Water Flow Sources for Human Activity Monitoring in Smart Homes.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- DSTGAT: A Spatio-Temporal Dynamic Graph Attention Network for User Activity Recognition.Sensors (Basel, Switzerland) · 2026Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a noninvasive system for identifying water flow sources with the final goal of supporting human activity recognition (HAR) in activities of daily living (ADL). The system employs a single microphone to capture ambient sounds within a room and detects active water sources based on their acoustic signatures. The audio signals are converted into time-resolved spectrograms, which are processed via time- and frequency-domain convolution and subsequently classified using a neural network. This approach enables both the identification of specific water sources, even combined, and the measurement of their usage duration with an overall accuracy of 90.6%. The study focuses on four common bathroom fixtures: toilet, bidet, shower, and washbasin. The proposed system is adaptable to various environments, requires no modifications to plumbing infrastructure, making it suitable for smart home and digital health applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.