A traffic-aware street lighting scheme for Smart Cities using autonomous networked sensors

被引:63
|
作者
Lau, Sei Ping [1 ]
Merrett, Geoff V. [1 ]
Weddell, Alex S. [1 ]
White, Neil M. [1 ]
机构
[1] Univ Southampton, Elect & Comp Sci, Southampton SO9 5NH, Hants, England
关键词
Adaptive street lighting; Smart streetlights; Smart Cities; Networked sensing; CONTROL-SYSTEM;
D O I
10.1016/j.compeleceng.2015.06.011
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Street lighting is a ubiquitous utility, but sustaining its operation presents a heavy financial and environmental burden. Many schemes have been proposed which selectively dim lights to improve energy efficiency, but little consideration has been given to the usefulness of the resultant street lighting system. This paper proposes a real-time adaptive lighting scheme, which detects the presence of vehicles and pedestrians and dynamically adjusts their brightness to the optimal level. This improves the energy efficiency of street lighting and its usefulness; a streetlight utility model is presented to evaluate this. The proposed scheme is simulated using an environment modelling a road network, its users, and a networked communication system - and considers a real streetlight topology from a residential area. The proposed scheme achieves similar or improved utility to existing schemes, while consuming as little as 1-2% of the energy required by conventional and state-of-the-art techniques. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:192 / 207
页数:16
相关论文
共 38 条
  • [1] Advanced Adaptive Street Lighting Systems for Smart Cities
    Gagliardi, Gianfranco
    Lupia, Marco
    Cario, Gianni
    Tedesco, Francesco
    Cicchello Gaccio, Francesco
    Lo Scudo, Fabrizio
    Casavola, Alessandro
    SMART CITIES, 2020, 3 (04): : 1495 - 1512
  • [2] Traffic-Aware Video Streaming Topology Reconfiguration for Smart City Applications
    Li, Guo-Hao
    Chiang, Yu-Ting
    Wang, Chao
    2024 13TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING, MECO 2024, 2024, : 4 - 7
  • [3] An optimization tool for energy efficiency of street lighting systems in smart cities
    Carli, Raffaele
    Dotoli, Mariagrazia
    Cianci, Edmondo
    IFAC PAPERSONLINE, 2017, 50 (01): : 14460 - 14464
  • [4] An Economic Evaluation of an Intelligent Street Lighting System for Smart Cities Context and Applications
    Carvalho, Lucas F. D. F.
    Damasceno, Luiz Wictor S.
    Carneiro, Ulisses F. G.
    Pinto, Milena Faria
    Melo, Aurelio G.
    Botelho, Daniel
    Moraes, Camile A.
    2021 14TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON), 2021, : 1340 - 1345
  • [5] TRADER: Traffic Light Phases Aware Driving for Reduced Traffic Congestion in Smart Cities
    Rhodes, Cullen
    Djahel, Soufiene
    2017 INTERNATIONAL SMART CITIES CONFERENCE (ISC2), 2017,
  • [6] A Soft Context-Aware Traffic Management System for Smart Cities
    Carneiro, Davide
    Amaral, Antonio
    Carvalho, Mariana
    INTELLIGENT ENVIRONMENTS 2020, 2020, 28 : 187 - 196
  • [7] Performance Analysis of a Smart Street Lighting application using LoRaWan
    Sarr, Yaye
    Gueye, Bamba
    Sarr, Cheikh
    2019 INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGIES AND NETWORKING (COMMNET), 2019, : 62 - 67
  • [8] Using Classification for Traffic Prediction in Smart Cities
    Christantonis, Konstantinos
    Tjortjis, Christos
    Manos, Anastassios
    Filippidou, Despina Elizabeth
    Mougiakou, Eleni
    Christelis, Evangelos
    ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2020, PT I, 2020, 583 : 52 - 61
  • [9] Techno-Economic and Social Aspects of Smart Street Lighting for Small Cities - A Case Study
    Akindipe, Dayo
    Olawale, Opeoluwa Wonuola
    Bujko, Richard
    SUSTAINABLE CITIES AND SOCIETY, 2022, 84
  • [10] A Data-Emergency-Aware Scheduling Scheme for Internet of Things in Smart Cities
    Qiu, Tie
    Zheng, Kaiyu
    Han, Min
    Chen, C. L. Philip
    Xu, Meiling
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (05) : 2042 - 2051