Prototyping a Gesture-Controlled Smart Home Assistant - an IoT Integration Approach

The rise of IoT has revolutionized appliance management, but current voice-controlled systems face limitations in noisy environments and for individuals with hearing or speech impairments. Additionally, integrating different connectivity methods for various appliances remains a challenge. This paper presents a gesture-controlled smart home assistant designed to address these issues. By integrating MQTT, HTTP and Bluetooth protocols, the system offers flexible control of diverse smart home devices. Utilizing a Raspberry Pi 4B with OpenCV and MediaPipe for gesture recognition can increase accessibility for individuals with hearing or speech impairments. Experimental results validate its effectiveness in accurately recognizing gestures and managing appliances, improving user interaction with smart home technologies in varied environments.

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Publication Details

Published
2024-11-14
DOI
https://doi.org/10.1109/incit63192.2024.10810656
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Prototyping a Gesture-Controlled Smart Home Assistant - an IoT Integration Approach

Derek S. Hernandez, Chin‐Kun Hu, Yu‐Kuen Lai, Chun-Hung Wu et al.
Hand Gesture Recognition Systems
article

Prototyping a Gesture-Controlled Smart Home Assistant - an IoT Integration Approach

Derek S. Hernandez, Chin‐Kun Hu, Yu‐Kuen Lai, Chun-Hung Wu, Wan-Ju Tu
article en

Abstract

The rise of IoT has revolutionized appliance management, but current voice-controlled systems face limitations in noisy environments and for individuals with hearing or speech impairments. Additionally, integrating different connectivity methods for various appliances remains a challenge. This paper presents a gesture-controlled smart home assistant designed to address these issues. By integrating MQTT, HTTP and Bluetooth protocols, the system offers flexible control of diverse smart home devices. Utilizing a Raspberry Pi 4B with OpenCV and MediaPipe for gesture recognition can increase accessibility for individuals with hearing or speech impairments. Experimental results validate its effectiveness in accurately recognizing gestures and managing appliances, improving user interaction with smart home technologies in varied environments.

Chung Yuan Christian University (TW)
Openalex Percentile: Top 75%
Hand Gesture Recognition Systems
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