Real-time energy efficiency analysis of buildings using ir imaging and computer vision
Reducing consumption of energy and emissions of greenhouse gas emissions is a critical worldwide problem, with the buildings’ sector accounting for up to 44% of fossil fuel consumption. Residential buildings, in particular, have great technical potential for energy savings. Our study addresses this...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/08/e3sconf_eenviro2024_01007.pdf |
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| Summary: | Reducing consumption of energy and emissions of greenhouse gas emissions is a critical worldwide problem, with the buildings’ sector accounting for up to 44% of fossil fuel consumption. Residential buildings, in particular, have great technical potential for energy savings. Our study addresses this by creating a model for real-time energy efficiency analysis of building insulation using infrared imagery and computer vision. The model monitors and offers important insights of energy transfer by continually evaluating a building’s thermal envelope. Additionally, an experimental stand comprising of a miniature model house made from different materials and insulation types, an IR camera and a Raspberry Pi were considered. It will provide data for an AI based model, which employs a robust and already proven architecture, YOLOv8 namely, used to determine the thermal characteristics of the analysed materials and the energy performances respectively. |
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| ISSN: | 2267-1242 |