Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11960/4019
Title: Hybrid building occupancy estimation using thermal imaging and environmental sensing
Authors: Barros, Daniel S.
Cruz, António Miguel
Lopes, Sérgio Ivan
Keywords: Building occupancy estimation
Indoor air quality
Carbon-dioxide
Thermal imaging
Issue Date: 2023
Publisher: IEEE
Citation: 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
Abstract: 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
Appears in Collections:ADiT-Lab - Publicações indexadas à WoS/Scopus
ESTG - Publicações indexadas à WoS/Scopus

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