Abstract
The European Union has been making efforts to increase energy efficiency within its member states, in line with most of the industrialized countries. In these efforts, the energy consumed by public lighting networks is a key target as it represents approximately 50% of the electricity consumption of European cities. In this paper we propose an approach for the autonomous management of public lighting networks in which each luminary is managed individually and that takes into account both their individual characteristics as well as ambient data. The approach is compared against a traditional management scheme, leading to a reduction in energy consumption of 28%.
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Acknowledgments
This work is co-funded by Fundos Europeus Estruturais e de Investimento (FEEI) through Programa Operacional Regional Norte, in the scope of project NORTE-01-0145-FEDER-023577 and by national funds through FCT – Fundação para a Ciência e Tecnologia through projects UID/CEC/00319/2019 and UIDB/04728/2020.
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Nunes, D., Teixeira, D., Carneiro, D., Sousa, C., Novais, P. (2020). Decision Intelligence in Street Lighting Management. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1160. Springer, Cham. https://doi.org/10.1007/978-3-030-45691-7_47
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DOI: https://doi.org/10.1007/978-3-030-45691-7_47
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