MAS Concept for PIR Sensor-Based Lighting System Control Applications

Kviesis, Krists; Adrian, Leslie R.; Avotiņš, Ansis; Tetervenoks, Oļegs; Repole, Donato

doi:10.1109/aieee51419.2021.9435749

Cited by 3 publications

(1 citation statement)

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“…Their experiment on a small traffic network demonstrated significant energy reductions. Similarly, Kviesis et al [167], developed a SSL control framework using a MAS that communicated with a cloud-based central control system. The system employed an adaptive fuzzy logic rule block in a cost-effective FPGA for decentralized control, enabling self-adaptation and learning based on weight change commands from the cloud.…”

Section: User-driven Controlmentioning

confidence: 99%

Smart Street Light Control: A Review on Methods, Innovations, and Extended Applications

Agramelal,

Sadik,

Moubarak

et al. 2023

Energies

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As urbanization increases, streetlights have become significant consumers of electrical power, making it imperative to develop effective control methods for sustainability. This paper offers a comprehensive review on control methods of smart streetlight systems, setting itself apart by introducing a novel light scheme framework that provides a structured classification of various light control patterns, thus filling an existing gap in the literature. Unlike previous studies, this work dives into the technical specifics of individual research papers and methodologies, ranging from basic to advanced control methods like computer vision and deep learning, while also assessing the energy consumption associated with each approach. Additionally, the paper expands the discussion to explore alternative functionalities for streetlights, such as serving as communication networks, environmental monitors, and electric vehicle charging stations. This multidisciplinary research aims to be a pivotal resource for both academics and industry professionals, laying the groundwork for future innovation and sustainable solutions in urban lighting.

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Section: User-driven Controlmentioning

confidence: 99%