An Intelligent System for Light and Air Conditioner Control Using YOLOv8
High energy consumption in classrooms is a significant concern, often resulting from inefficient lighting and air conditioning systems. Specifically, the problem lies in the lack of automated control mechanisms that adjust energy use based on real-time occupancy data. This study aims to develop and...
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| Format: | Article |
| Language: | English |
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Pusat Penelitian dan Pengabdian Masyarakat (P3M), Politeknik Negeri Cilacap
2024-12-01
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| Series: | Journal of Innovation Information Technology and Application |
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| Online Access: | https://ejournal.pnc.ac.id/index.php/jinita/article/view/2446 |
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| _version_ | 1850094746008027136 |
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| author | Ikharochman Tri Utomo Muhammad Nauval Firdaus Sisdarmanto Adinandra Suatmi Murnani |
| author_facet | Ikharochman Tri Utomo Muhammad Nauval Firdaus Sisdarmanto Adinandra Suatmi Murnani |
| author_sort | Ikharochman Tri Utomo |
| collection | DOAJ |
| description | High energy consumption in classrooms is a significant concern, often resulting from inefficient lighting and air conditioning systems. Specifically, the problem lies in the lack of automated control mechanisms that adjust energy use based on real-time occupancy data. This study aims to develop and evaluate a system that employs a camera integrated with the YOLOv8 algorithm to detect human presence and optimize energy usage by controlling lights and air conditioning. The system's performance was assessed in three different classroom environments: two large and one small. The system's accuracy for occupancy detection varied from 13.64% to 100%, depending on lighting conditions and room size. Light control accuracy was highest in the classrooms with consistent lighting, reaching 99.77%. Air conditioning control achieved perfect accuracy of 100% in the classroom with a SHARP brand AC, with a maximum remote-control range of 7 meters. These findings indicate that the system's performance is influenced by lighting conditions and room size, with smaller rooms showing better results. The system demonstrates promising potential for reducing energy consumption in classroom settings, thereby contributing to more sustainable energy practices. |
| format | Article |
| id | doaj-art-107d9e94b60c460e8f40083c71d92ccc |
| institution | DOAJ |
| issn | 2716-0858 2715-9248 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Pusat Penelitian dan Pengabdian Masyarakat (P3M), Politeknik Negeri Cilacap |
| record_format | Article |
| series | Journal of Innovation Information Technology and Application |
| spelling | doaj-art-107d9e94b60c460e8f40083c71d92ccc2025-08-20T02:41:36ZengPusat Penelitian dan Pengabdian Masyarakat (P3M), Politeknik Negeri CilacapJournal of Innovation Information Technology and Application2716-08582715-92482024-12-016214115210.35970/jinita.v6i2.24462446An Intelligent System for Light and Air Conditioner Control Using YOLOv8Ikharochman Tri Utomo0Muhammad Nauval Firdaus1Sisdarmanto Adinandra2Suatmi Murnani3Universitas Islam IndonesiaUniversitas Islam IndonesiaUniversitas Islam IndonesiaUniversitas Islam IndonesiaHigh energy consumption in classrooms is a significant concern, often resulting from inefficient lighting and air conditioning systems. Specifically, the problem lies in the lack of automated control mechanisms that adjust energy use based on real-time occupancy data. This study aims to develop and evaluate a system that employs a camera integrated with the YOLOv8 algorithm to detect human presence and optimize energy usage by controlling lights and air conditioning. The system's performance was assessed in three different classroom environments: two large and one small. The system's accuracy for occupancy detection varied from 13.64% to 100%, depending on lighting conditions and room size. Light control accuracy was highest in the classrooms with consistent lighting, reaching 99.77%. Air conditioning control achieved perfect accuracy of 100% in the classroom with a SHARP brand AC, with a maximum remote-control range of 7 meters. These findings indicate that the system's performance is influenced by lighting conditions and room size, with smaller rooms showing better results. The system demonstrates promising potential for reducing energy consumption in classroom settings, thereby contributing to more sustainable energy practices.https://ejournal.pnc.ac.id/index.php/jinita/article/view/2446classroomcomputer visionenergy consumptionoccupancy detectionyolo |
| spellingShingle | Ikharochman Tri Utomo Muhammad Nauval Firdaus Sisdarmanto Adinandra Suatmi Murnani An Intelligent System for Light and Air Conditioner Control Using YOLOv8 Journal of Innovation Information Technology and Application classroom computer vision energy consumption occupancy detection yolo |
| title | An Intelligent System for Light and Air Conditioner Control Using YOLOv8 |
| title_full | An Intelligent System for Light and Air Conditioner Control Using YOLOv8 |
| title_fullStr | An Intelligent System for Light and Air Conditioner Control Using YOLOv8 |
| title_full_unstemmed | An Intelligent System for Light and Air Conditioner Control Using YOLOv8 |
| title_short | An Intelligent System for Light and Air Conditioner Control Using YOLOv8 |
| title_sort | intelligent system for light and air conditioner control using yolov8 |
| topic | classroom computer vision energy consumption occupancy detection yolo |
| url | https://ejournal.pnc.ac.id/index.php/jinita/article/view/2446 |
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