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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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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...

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Published in: Electronics
ISSN: 2079-9292
Published: MDPI AG 2025
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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. 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spelling 2025-10-10T15:49:35.5952547 v2 70257 2025-09-03 A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control 1f6b6bce676ade8b4854d4f4f7cd7ce7 0000-0003-0830-2647 Nora Almania Nora Almania true false e1525e1e38ade4a94f7c0d2640efb1eb 0000-0002-2300-3031 Sarah Alhouli Sarah Alhouli true false c7b57876957049ac9718ff1b265fb2ce 0000-0002-4421-7549 Deepak Sahoo Deepak Sahoo true false 2025-09-03 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. Journal Article Electronics 14 18 3576 MDPI AG 2079-9292 visible light sensing; photovoltaic light sensor; hovering hand gesture recognition; machine learning pipeline; real-time model evaluation; smart home control; user experience evaluation 9 9 2025 2025-09-09 10.3390/electronics14183576 COLLEGE NANME COLLEGE CODE Swansea University Other This research was funded by Swansea University by the Engineering and Physical Sciences Research Council grant (EPSRC) EP/W025396/1. 2025-10-10T15:49:35.5952547 2025-09-03T19:03:44.1937511 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Nora Almania 0000-0003-0830-2647 1 Sarah Alhouli 0000-0002-2300-3031 2 Deepak Sahoo 0000-0002-4421-7549 3 70257__35314__93d72cebb98f4badbc1e74045568b8b6.pdf 70257.VoR.pdf 2025-10-10T15:42:35.5586231 Output 16338830 application/pdf Version of Record true © 2025 by the authors. This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. true eng https://creativecommons.org/licenses/by/4.0/ 331
title A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
spellingShingle A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
Nora Almania
Sarah Alhouli
Deepak Sahoo
title_short A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
title_full A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
title_fullStr A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
title_full_unstemmed A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
title_sort A Photovoltaic Light Sensor-Based Self-Powered Real-Time Hover Gesture Recognition System for Smart Home Control
author_id_str_mv 1f6b6bce676ade8b4854d4f4f7cd7ce7
e1525e1e38ade4a94f7c0d2640efb1eb
c7b57876957049ac9718ff1b265fb2ce
author_id_fullname_str_mv 1f6b6bce676ade8b4854d4f4f7cd7ce7_***_Nora Almania
e1525e1e38ade4a94f7c0d2640efb1eb_***_Sarah Alhouli
c7b57876957049ac9718ff1b265fb2ce_***_Deepak Sahoo
author Nora Almania
Sarah Alhouli
Deepak Sahoo
author2 Nora Almania
Sarah Alhouli
Deepak Sahoo
format Journal article
container_title Electronics
container_volume 14
container_issue 18
container_start_page 3576
publishDate 2025
institution Swansea University
issn 2079-9292
doi_str_mv 10.3390/electronics14183576
publisher MDPI AG
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
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description 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.
published_date 2025-09-09T09:15:32Z
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