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

Lau, Sei Ping; Merrett, Geoff V.; Weddell, Alex S.; White, Neil

doi:10.1016/j.compeleceng.2015.06.011

Cited by 85 publications

(44 citation statements)

References 27 publications

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“…This phenomenon will have increasing importance in future cities to monitor existing conditions for efficient use of capital and natural resources or controlling traffic flow through wireless sensor networks [141][142][143]. In addition it will allow modifying energy usage or household waste of urban dwellings with real time feedback [144][145][146][147].…”

Section: Administering Future Citiesmentioning

confidence: 99%

Future cities and environmental sustainability

Riffat

Powell

Aydın

2016

Future Cities and Environment

101

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Massive growth is threatening the sustainability of cities and the quality of city life. Mass urbanisation can lead to social instability, undermining the capacity of cities to be environmentally sustainable and economically successful. A new model of sustainability is needed, including greater incentives to save energy, reduce consumption and protect the environment while also increasing levels of citizen wellbeing. Cities of the future should be a socially diverse environment where economic and social activities overlap and where communities are focused around neighbourhoods. They must be developed or adapted to enable their citizens to be socioeconomically creative and productive. Recent developments provide hope that such challenges can be tackled. This review describes the exciting innovations already being introduced in cities as well as those which could become reality in the near future.

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Section: Administering Future Citiesmentioning

confidence: 99%

Future cities and environmental sustainability

Riffat

Powell

Aydın

2016

Future Cities and Environment

101

View full text Add to dashboard Cite

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“…Such solutions can be applied at the scale of an entire city [12], a single block, or indoor [13][14][15]. They are often based on rules and configured for particular deployments [16][17][18][19]. However, a lack of underlying formal models often results in harder and more costly adjustment to evolving requirements or deployment at new locations.…”

Section: Motivation and Related Researchmentioning

confidence: 99%

Improving Control Efficiency of Dynamic Street Lighting by Utilizing the Dual Graph Grammar Concept

Wojnicki

Kotulski

2018

Energies

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Abstract:The paper introduces a definition of dual graph grammar. It enables two graphs to share information in a synchronized way. A smart city example application, which is an outdoor lighting control system utilizing the dual graph grammar, is also demonstrated. The system controls dimming of street lights which is based on traffic intensity. Each luminaire's light level is adjusted individually to comply with the lighting norms to ensure safety. Benefits of applying the dual graph grammar are twofold. First, it increases expressive power of the mathematical model that the system uses. It becomes possible to take into account complex geographical distribution of sensors and logical dependencies among them. Second, it increases the system's efficiency by reducing the problem size during run-time. Experimental results show a reduction of the computation time by a factor of 2.8. The approach has been verified in practice.

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“…Furthermore, the model can be easily deployed in new locations, just by introducing topological relationships among segments, detectors and luminaires. For comparison, such new deployments with other smart lighting control solutions [17][18][19] are usually challenging-each deployment needs to be analyzed case by case and appropriately configured, which takes time and is costly. "dt": traffic intensity detector; "s": street segment; "m2", "m3" and "m4": lighting classes; "c": luminaire configuration; "l": luminaire; "p()": power settings as percentage of the luminaire's nominal power.…”

Section: Dynamic Control Conceptmentioning

confidence: 99%

Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland

Wojnicki

Kotulski

2018

Sustainability

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Abstract:The deployment of dynamic street lighting, which adjusts lighting levels to fulfill particular needs, leads to energy savings. These savings contribute to the overall lighting infrastructure maintenance cost. Yet another contribution is the cost of traffic intensity data. The data is read directly from sensor systems or intelligent transportation systems (ITSs). The more frequent the readings are, the more costly they become, because of hardware capabilities, data transfer and software license costs, among others. The paper investigates a relationship between the frequency of readings, in particular the averaging window size and step, and achieved energy savings. It is based on a simulation, taking into account a representative part of a city and traffic intensity data, which span over a period of one year. While the energy consumption reduction is simulated, all data, including each luminaire power setting, induction loop locations and street characteristics, come from a representative sample of the city of Krakow, Poland. Controlling the power settings complies with the lighting standard CEN/TR 13201. Analysis of the outcomes indicates that the shorter the window size or step are, the more energy saving that is available. In particular, for the previous standard CEN/TR 13201 2004, having the window size and step at 15 min results in 26.75% of energy saving, while reducing these values to 6 min provides 27%. Savings are more profound for the current standard (CEN/TR 13201 2014), assuming a 15 min size and step results in 47.43%, while having a 6 min size and step provides 47.69%. The results can serve as a guideline for identifying the economic viability of dynamic lighting control systems. Additionally, it can be observed that the current lighting standard provides far greater potential for dynamic control then the previous standard.

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

Cited by 85 publications

References 27 publications

Future cities and environmental sustainability

Future cities and environmental sustainability

Improving Control Efficiency of Dynamic Street Lighting by Utilizing the Dual Graph Grammar Concept

Empirical Study of How Traffic Intensity Detector Parameters Influence Dynamic Street Lighting Energy Consumption: A Case Study in Krakow, Poland

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