| Issue |
E3S Web Conf.
Volume 672, 2025
The 17th ROOMVENT Conference (ROOMVENT 2024)
|
|
|---|---|---|
| Article Number | 01055 | |
| Number of page(s) | 8 | |
| Section | Indoor Climate: Thermal Comfort | |
| DOI | https://doi.org/10.1051/e3sconf/202567201055 | |
| Published online | 05 December 2025 | |
Development of Low-Cost IoT Units for Thermal Comfort Measurement and AC Energy Consumption Prediction System
1 Kyushu University, Graduate School of Human-Environment Studies, Japan
2 Kyushu University, Faculty of Human-Environment Studies, Japan
3 Kagawa University, Faculty of Engineering and Design, Japan
4 Waseda University, Faculty of Science and Engineering, School of Creative Science and Engineering, Japan
5 Sojo University, Faculty of Engineering Department of Architecture, Japan
* Corresponding author: chen.yutong.262@s.kyushu-u.ac.jp
In response to the substantial energy consumption in buildings, the Japanese government initiated the BI-Tech (Behavioral Insights X Technology) project in 2019, aimed at promoting voluntary energy-saving behaviors through the utilization of AI and IoT technologies. Our study aimed at small and medium-sized office buildings introduces a cost-effective IoT-based BI-Tech system, utilizing the Raspberry Pi 4B+ platform for real-time monitoring of indoor thermal conditions and air conditioner (AC) set-point temperature. Employing machine learning and image recognition, the system analyzes data to calculate the PMV index and predict energy consumption changes due to temperature adjustments. The integration of mobile and desktop applications conveys this information to users, encouraging energy-efficient behavior modifications. The machine learning model achieved with an R2 value of 97%, demonstrating the system’s efficiency in promoting energy-saving habits among users.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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