A Complete Hardware Setup for Smart Lighting System

Kumar, Arun; Shareef, Arish; Harn, Koh Tsyr; Kar, Pushpendu; Panda, Sanjib Kumar

doi:10.1109/icsets.2019.8744873

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…In recent years, the topic of urban smart lighting gained attention and several aspects of this technology were investigated separately. Some papers deal with the design of the hardware (e.g., light controller, lamp driver) [37][38][39][40][41], whereas other papers deal with the automatic, context aware, control of illumination [29,42,43]. There are papers concerning software/cloud-computing issues in smart city scenarios [44][45][46], others focusing on energy efficiency [47][48][49][50][51][52], as well as paper presenting smart lighting solutions based on specific communication technologies [53][54][55][56][57].…”

Section: Related Workmentioning

confidence: 99%

Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems

Pasolini

Toppan²,

Zabini

et al. 2019

Applied Sciences

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Street lighting characterizes many smart city initiatives around the world. In fact, significant savings can be achieved by not only replacing traditional luminaires with low-power LEDs, but also providing streetlights with smart light controllers and network connectivity, allowing the introduction of a sensible light intensity management and reduction of maintenance costs. Moreover, if designed with a far-looking view, smart lighting infrastructure could also support city-wide Internet of Things services, becoming key enablers of the smart city revolution, also in the 5G perspective. In this paper, we provide a thorough discussion on network architectures and communication technologies that could be adopted for smart public lighting applications, showing their benefits and downsides. Starting with significant activity on research, implementation and in-field testing, we also outline the steps required for the deployment of a smart public lighting infrastructure, each discussed in accordance with the network topology considered. Finally, we introduce some additional services that a smart public lighting infrastructure could support and discuss the benefits that would arise from integration with the upcoming 5G cellular network.In this framework, the momentum for smart public lighting is mounting, as several trials and large-scale implementations showed their effectiveness [5]. In particular, LED fixtures are expected to dramatically reduce urban electricity costs, now due to street lighting for a share of 40% [6]. Smart luminaires will dynamically adapt lighting to actual needs, for instance lowering the lumen output when there are low traffic volumes and good visibility conditions are detected.Important references in this regard are the "GPP Revision of the EU Green Public Procurement Criteria for Road Lighting and traffic signals" [7], authored by the Joint Research Centre (JRC) of the European Commission, and the CEN/TR 13201 lighting standards [8][9][10][11][12], which define how to properly design lighting systems. As reported in Reference [7], "due to the multiple benefits of dimming, dimming controls must be installed in all cases unless, in exceptional circumstances, it can be demonstrated that the total cost of ownership would increase by installing dimming controls. The EN 13201 standard itself [8][9][10][11][12] recognizes that the required lighting levels are dynamic in nature and an appropriate lighting level at all times can only be ensured with adequate dimming control during off-peak hours. Dimming has obvious environmental benefits via lower energy consumption and reduced light pollution. Furthermore, dimming can enhance the lifetime of LED luminaires due to a reduced risk of overheating, which is the principal cause of abrupt LED failure." In this regard, results from a global trial of LED streetlights show that, when coupled with smart controls, LED fixtures can deliver electricity savings of up to 80% over classic lighting technologies [13].Beyond energy savings, since each smart streetlight n...

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Section: Related Workmentioning

confidence: 99%

Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems

Pasolini

Toppan²,

Zabini

et al. 2019

Applied Sciences

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Comprehensive Assessment of Context-Adaptive Street Lighting: Technical Aspects, Economic Insights, and Measurements from Large-Scale, Long-Term Implementations

Pasolini,

Toppan,

Toppan

et al. 2024

Sensors

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This paper addresses the growing importance of efficient street lighting management, driven by rising electricity costs and the need for municipalities to implement cost-effective solutions. Central to this study is the UNI 11248 Italian regulation, which extends the European EN 13201-1 standard introduced in 2016. These standards provide guidelines for designing, installing, operating, and maintaining lighting systems in pedestrian and vehicular traffic areas. Specifically, the UNI 11248 standard introduces the possibility to dynamically adjust light intensity through two alternative operating modes: (a) Traffic Adaptive Installation (TAI), which dims the light based solely on real-time traffic flow measurements; and (b) Full Adaptive Installation (FAI), which, in addition to traffic measurements, also requires evaluating road surface luminance and meteorological conditions. In this paper, we first present the general architecture and operation of an FAI-enabled lighting infrastructure, which relies on environmental sensors and a heterogeneous wireless communication network to connect intelligent, remotely controlled streetlights. Subsequently, we examine large-scale, in-field FAI infrastructures deployed in Vietnam and Italy as case studies, providing substantial measurement data. The paper offers insights into the measured energy consumption of these infrastructures, comparing them to that of conventional light-control strategies used in traditional installations. The measurements demonstrate the superiority of FAI as the most efficient solution.

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Fuzzy-based smart system for controlling road lights

Satam¹

2022

Vojnotehnički glasnik

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Introduction: The energy consumed for street lighting is a major expenditure in urban environments. According to the World Bank, it constitutes up to 65% of cities' electricity costs and 10% of their overall budgets. The demand for lighting is growing significantly due to rapid urbanization, thus eating up even more energy and money - unless smarter solutions are deployed to reduce costs. Method: In this paper, a model for street lighting was established, consisting of several lamp posts on both sides of the street. The model was the exact replica of the street lighing system inside the city of Kirkuk, Iraq. The number of objects passing along the street was monitored, both during and out of rush hours. This all was taken into account in the energy consumption calculation. The controller used for this model is Arduino UNO. The Arduino receives signals from 3 IR sensors, processes these signals, and then sends the action to the lamp posts. Fuzzy logic was applied in two cases: the first one is during the daylight, the second one is during the sunrise and the sunset, to control the intensity of the light of the lamp posts. Results: Both cases showed significant results regarding the reliability, efficiency, and countability of the system in decreasing the level of energy consumption. Conclusion: The system can be applicable for smart city projects. It is efficient, cost effective and shows reliable results in saving energy.

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A Complete Hardware Setup for Smart Lighting System

Cited by 3 publications

References 5 publications

Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems

Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems

Comprehensive Assessment of Context-Adaptive Street Lighting: Technical Aspects, Economic Insights, and Measurements from Large-Scale, Long-Term Implementations

Fuzzy-based smart system for controlling road lights

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