Real-Time Acoustic Scene Recognition for Elderly Daily Routines Using Edge-Based Deep Learning DOI Creative Commons
Hongyu Yang,

Ronald Y. Dong,

Rong Guo

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(6), P. 1746 - 1746

Published: March 12, 2025

The demand for intelligent monitoring systems tailored to elderly living environments is rapidly increasing worldwide with population aging. Traditional acoustic scene that rely on cloud computing are limited by data transmission delays and privacy concerns. Hence, this study proposes an recognition system integrates edge deep learning enable real-time of individuals’ daily activities. consists low-power devices equipped multiple microphones, portable wearable components, compact power modules, ensuring its seamless integration into the lives elderly. We developed four models—convolutional neural network, long short-term memory, bidirectional network—and used model quantization techniques reduce computational complexity memory usage, thereby optimizing them meet device constraints. CNN demonstrated superior performance compared other models, achieving 98.5% accuracy, inference time 2.4 ms, low requirements (25.63 KB allocated Flash 5.15 RAM). This architecture provides efficient, reliable, user-friendly solution in care.

Language: Английский

Internet of Robotic Things: Current Technologies, Challenges, Applications, and Future Research Topics DOI Creative Commons
Jakub Krejčí, Marek Babiuch, Jiří Suder

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(3), P. 765 - 765

Published: Jan. 27, 2025

This article focuses on the integration of Internet Things (IoT) and Robotic Things, representing a dynamic research area with significant potential for industrial applications. The (IoRT) integrates IoT technologies into robotic systems, enhancing their efficiency autonomy. provides an overview used in IoRT, including hardware components, communication technologies, cloud services. It also explores IoRT applications industries such as healthcare, agriculture, more. discusses challenges future directions, data security, energy efficiency, ethical issues. goal is to raise awareness importance demonstrate how this technology can bring benefits across various sectors.

Language: Английский

Citations

2
Real-Time Acoustic Scene Recognition for Elderly Daily Routines Using Edge-Based Deep Learning DOI Creative Commons
Hongyu Yang,

Ronald Y. Dong,

Rong Guo

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(6), P. 1746 - 1746

Published: March 12, 2025

The demand for intelligent monitoring systems tailored to elderly living environments is rapidly increasing worldwide with population aging. Traditional acoustic scene that rely on cloud computing are limited by data transmission delays and privacy concerns. Hence, this study proposes an recognition system integrates edge deep learning enable real-time of individuals’ daily activities. consists low-power devices equipped multiple microphones, portable wearable components, compact power modules, ensuring its seamless integration into the lives elderly. We developed four models—convolutional neural network, long short-term memory, bidirectional network—and used model quantization techniques reduce computational complexity memory usage, thereby optimizing them meet device constraints. CNN demonstrated superior performance compared other models, achieving 98.5% accuracy, inference time 2.4 ms, low requirements (25.63 KB allocated Flash 5.15 RAM). This architecture provides efficient, reliable, user-friendly solution in care.

Language: Английский

Citations

0