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Advisor(s)
Abstract(s)
In the past few decades, the urbanization area increased significantly, requiring enhanced services and applications to improve the lifestyle of its citizens. Lighting is one of the most relevant infrastructures
due to its impact on modern societies, but it is also complex to manage them in cities since it involves a massive number of widespread posts and is costly as the result of the consumption of significant amounts of
energy. In that regard, this work proposes a scalable framework to manage a significant huge number of lamp posts. Its purpose is to give support to collecting large amounts of sensor data to help to analyze and efficiently
fit the light intensity level to the space the posts are covering. Luminosity sensors are used to optimize the intensity of light needed in the urban areas. The proposed framework explores the concept of smart cities by
combining the data collected from sensors plugged into IoT (Internet-ofThings) devices. The proposed framework offers the capability to extend and integrate new services to different domains with each other which
enhances the quality and performance of urban services. To demonstrate the feasibility of the framework, a simulation was put in place.
Description
Keywords
Smart Cities Smart lights Sensors Scalability
Citation
Rebelo, J., Rodrigues, R., Henriques, J., Cardoso, F., Wanzeller, C. & Caldeira, F. (2023). A scalable smart lighting framework to save energy In: D. H. de la Iglesia, J. F. de Paz Santana, A.J. López Rivero (Eds.), New Trends in Disruptive Technologies,Tech Ethics and Artificial Intelligence. DiTTEt 2022. Advances in Intelligent Systems and Computing, vol 1430 (pp.286–292). Springer. doi: https://doi.org/10.1007/978-3-031-14859-0_26