Utilize este identificador para referenciar este registo:
http://hdl.handle.net/20.500.11960/4019| Título: | Hybrid building occupancy estimation using thermal imaging and environmental sensing |
| Autores: | Barros, Daniel S. Cruz, António Miguel Lopes, Sérgio Ivan |
| Palavras-chave: | Building occupancy estimation Indoor air quality Carbon-dioxide Thermal imaging |
| Data: | 2023 |
| Editora: | IEEE |
| Citação: | Barros, D. S., Cruz, A. M. R., & Lopes, S. I. (2023). Hybrid building occupancy estimation using thermal imaging and environmental sensing. In Proceedings of the IEEE International Conference on Industrial Technology, ICIT 2023, 4-6 april, 2023, Orlando (pp. 1-6). IEEE. https://doi.org/10.1109/ICIT58465.2023.10143114 |
| Resumo: | Estimating building occupancy is a fundamental aspect of effective building management. By predicting building occupancy over time, we may reduce energy consumption, and contribute to energy efficiency in buildings. Building Occupancy Estimation (BOE) can be useful to compute building management metrics, such as the number of users in each room during work hours or in the entire building overnight. This paper presents a Hybrid Building Occupancy Estimation (HBOE) method that uses thermal imaging and environmental sensing to deliver a qualitative occupancy metric. Results show that the chosen approach represents a cost-effective solution, delivering an indicative BOE value based on thermal imaging and environmental sensing. |
| URI: | http://hdl.handle.net/20.500.11960/4019 |
| ISBN: | 979-8-3503-3650-4 |
| Aparece nas colecções: | ADiT-Lab - Publicações indexadas à WoS/Scopus ESTG - Publicações indexadas à WoS/Scopus |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| Hybrid_Building_Occupancy_Estimation_using_Thermal_Imaging_and_Environmental_Sensing.pdf | 350.66 kB | Adobe PDF | Ver/Abrir |
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