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Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

Yu-Liang Hsu¹, Po-Huan Chou², Hsing-Cheng Chang³

¹Department of Automatic Control Engineering, Feng Chia University (FCU), No. 100, Wenhwa Road, Seatwen, Taichung 40724, Taiwan. hsuyl@fcu.edu.tw.

Sensors (Basel, Switzerland)

|July 18, 2017

Summary

This study introduces a smart home system using wearable sensors and AI for appliance control, indoor navigation, and safety. The integrated system achieved high accuracy in gesture recognition, indoor positioning, and fire detection for enhanced living environments.

Keywords:

artificial intelligence gesture recognition home safety indoor positioning sensing data fusion smart energy management smart home automation wearable intelligent technology

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Area of Science:

Smart Home Technology
Artificial Intelligence
Wearable Sensors
Data Fusion

Background:

Traditional smart home systems lack integrated functionality for comprehensive user interaction and environmental monitoring.
The need for intuitive control, efficient energy management, and robust safety features in modern homes is increasing.

Purpose of the Study:

To develop a multisensor data fusion-based smart home system integrating wearable technology, AI, and sensor fusion.
To create systems for automated appliance control via gesture recognition, indoor navigation for energy management, and home safety/fire detection.

Main Methods:

Development of wearable motion sensing devices for wrists (gesture recognition) and feet (indoor positioning).
Implementation of AI algorithms for 3D gesture recognition, indoor pedestrian navigation, and intelligent fire detection.
Integration of a multisensor circuit module and an intelligent monitoring interface for real-time data display.

Main Results:

Gesture recognition for appliance control achieved high accuracy (up to 95.3%) across various cross-validation methods.
Indoor positioning accuracy was approximately 3.36% of the traveled distance, with distance accuracy around 0.22%.
Home safety and fire detection system demonstrated 98.81% accuracy in identifying indoor environmental conditions.

Conclusions:

The developed multisensor data fusion technology effectively creates an intelligent smart home environment.
The integrated system offers a feasible and effective solution for automated control, energy management, and home safety.
Wearable technology combined with AI and sensor fusion significantly enhances smart home capabilities.