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A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control

Nora Almania Orcid Logo, Sarah Alhouli Orcid Logo, Deepak Sahoo Orcid Logo

Electronics, Volume: 14, Issue: 18, Start page: 3576

Swansea University Authors: Nora Almania Orcid Logo, Sarah Alhouli Orcid Logo, Deepak Sahoo Orcid Logo

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Abstract

Many gesture recognition systems with innovative interfaces have emerged for smart home control. However, these systems tend to be energy-intensive, bulky, and expensive. There is also a lack of real-time demonstrations of gesture recognition and subsequent evaluation of the user experience. Photovo...

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Published in: Electronics
ISSN: 2079-9292
Published: MDPI AG 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa70257
Abstract: Many gesture recognition systems with innovative interfaces have emerged for smart home control. However, these systems tend to be energy-intensive, bulky, and expensive. There is also a lack of real-time demonstrations of gesture recognition and subsequent evaluation of the user experience. Photovoltaic light sensors are self-powered, battery-free, flexible, portable, and easily deployable on various surfaces throughout the home. They enable natural, intuitive, hover-based interaction, which could create a positive user experience. In this paper, we present the development and evaluation of a real-time, hover gesture recognition system that can control multiple smart home devices via a self-powered photovoltaic interface. Five popular supervised machine learning algorithms were evaluated using gesture data from 48 participants. The random forest classifier achieved high accuracies. However, a one-size-fits-all model performed poorly in real-time testing. User-specific random forest models performed well with 10 participants, showing no significant difference in offline and real-time performance and under normal indoor lighting conditions. This paper demonstrates the technical feasibility of using photovoltaic surfaces as self-powered interfaces for gestural interaction systems that are perceived to be useful and easy to use. It establishes a foundation for future work in hover-based interaction and sustainable sensing, enabling human–computer interaction researchers to explore further applications.
Keywords: visible light sensing; photovoltaic light sensor; hovering hand gesture recognition; machine learning pipeline; real-time model evaluation; smart home control; user experience evaluation
College: Faculty of Science and Engineering
Funders: This research was funded by Swansea University by the Engineering and Physical Sciences Research Council grant (EPSRC) EP/W025396/1.
Issue: 18
Start Page: 3576