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A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
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Sarah Alhouli ,
Deepak Sahoo
Electronics, Volume: 14, Issue: 18, Start page: 3576
Swansea University Authors:
Nora Almania , Sarah Alhouli , Deepak Sahoo
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DOI (Published version): 10.3390/electronics14183576
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...
| Published in: | Electronics |
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| ISSN: | 2079-9292 |
| Published: |
MDPI AG
2025
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| Online Access: |
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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. |
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| 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 |