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

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