Cost analysis of smart lighting solutions for smart cities

Cacciatore, Giuseppe; Fiandrino, Claudio; Kliazovich, Dzmitry; Granelli, Fabrizio; Bouvry, Pascal

doi:10.1109/icc.2017.7996886

Cited by 39 publications

(26 citation statements)

References 19 publications

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“…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.…”

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confidence: 99%

“…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.…”

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confidence: 99%

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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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Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems

Pasolini

Toppan²,

Zabini

et al. 2019

Applied Sciences

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“…CrowdSenSim [17], the first simulator for MCS systems, was designed to fill this gap by providing the researchers a tool to perform large scale simulations over realistic urban environments. For example, its effectiveness has been demonstrated to evaluate performance of city-wide solutions for public street lighting [18].…”

Section: Introductionmentioning

confidence: 99%

Profiling Energy Efficiency of Mobile Crowdsensing Data Collection Frameworks for Smart City Applications

Tomasoni

Capponi

Fiandrino

et al. 2018

2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)

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Abstract-Mobile crowdsensing (MCS) has emerged in the last years and has become one of the most prominent paradigms for urban sensing. In MCS, citizens actively participate in the sensing process by contributing data with their smartphones, tablets, wearables and other mobile devices to a collector. As citizens sustain costs while contributing data, i.e., the energy spent from the batteries for sensing and reporting, devising energy efficient data collection frameworks (DCFs) is essential. In this work, we compare the energy efficiency of several DCFs through CrowdSenSim, which allows to perform largescale simulation experiments in realistic urban environments. Specifically, the DCFs under analysis differ one with each other by the data reporting mechanism implemented and the signaling between users and the collector needed for sensing and reporting decisions. Results reveal that the key criterion differentiating DCFs' energy consumption is the data reporting mechanism. In principle, continuous reporting to the collector should be more energy consuming than probabilistic reporting. However, DCFs with continuous reporting that implement mechanisms to block sensing and data delivery after a certain amount of contribution are more effective in harvesting data from the crowd.

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“…CrowdSenSim [15], the first simulator for MCS systems, was designed to fill this gap by providing the researchers a tool capable of performing large scale simulations over realistic urban environments. For example, its effectiveness has been demonstrated to evaluate performance of city-wide solutions for public street lighting [16], energy efficient data collection [17] and user recruitment in crowdsensing campaigns [18]. To perform effective simulations in complex environments, such as modern cities, the simulation platform has to be scalable while providing at the same time precise and detailed information.…”

Section: Introductionmentioning

confidence: 99%

“…The vertices of street network graphs have to be close one with each other to ensure high precision of the sequence of steps defining user trajectories. Furthermore, CrowdSenSim knows about the precise location of access points, e.g., 3G and WiFi, for communication purposes [27] and additional on-demand information typical of the application under investigation like the location of lampposts for public street lighting [16].…”

Section: Introductionmentioning

confidence: 99%

High-Precision Design of Pedestrian Mobility for Smart City Simulators

Vitello

Capponi

Fiandrino

et al. 2018

2018 IEEE International Conference on Communications (ICC)

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Abstract-The unprecedented growth of the population living in urban environments calls for a rational and sustainable urban development. Smart cities can fill this gap by providing the citizens with high-quality services through efficient use of Information and Communication Technology (ICT). To this end, active citizen participation with mobile crowdsensing (MCS) techniques is a becoming common practice. As MCS systems require wide participation, the development of large scale real testbeds is often not feasible and simulations are the only alternative solution. Modeling the urban environment with high precision is a key ingredient to obtain effective results. However, currently existing tools like OpenStreetMap (OSM) fail to provide sufficient levels of details. In this paper, we apply a procedure to augment the precision (AOP) of the graph describing the street network provided by OSM. Additionally, we compare different mobility models that are synthetic and based on a realistic dataset originated from a well known MCS data collection campaign (ParticipAct). For the dataset, we propose two arrival models that determine the users' arrivals and match the experimental contact distribution. Finally, we assess the scalability of AOP for different cities, verify popular metrics for human mobility and the precision of different arrival models.

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Cost analysis of smart lighting solutions for smart cities

Cited by 39 publications

References 19 publications

Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems

Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems

Profiling Energy Efficiency of Mobile Crowdsensing Data Collection Frameworks for Smart City Applications

High-Precision Design of Pedestrian Mobility for Smart City Simulators

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