Enabling IoT empowered smart lighting solutions: A communication theoretic perspective

Zaidi, Syed Ali Raza; Imran, Ali Shariq; McLernon, Des; Ghogho, Mounir

doi:10.1109/wcncw.2014.6934875

Cited by 12 publications

(4 citation statements)

References 10 publications

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“…Information that enters and leaves the system includes current sensor data and lamp control data [120]. DALI is an interface that provides interoperability in controlling lights from various products [121].…”

Section: ) Internet Of Thingsmentioning

confidence: 99%

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

et al. 2022

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Smart lighting has become a universal smart product solution, with global revenues of up to US$5.9 billion by 2021. Six main factors drive the technology: light-emitting diode (LED) lighting, sensors, control, analytics, and intelligence. The Internet of things (IoT) concept with the end device, platform, and application layer plays an essential role in optimizing the advantages of LED lighting in the emergence of smart lighting. The ultimate aim of smart lighting research is to introduce low energy efficiency and high user comfort, where the latter is still in the infancy stage. This paper presents a systematic literature review (SLR) from a bird's eye view covering full-length research topics on smart lighting, including issues, implementation targets, technological solutions, and prospects. In addition to that, this paper also provides a detailed and extensive overview of emerging machine learning techniques as a key solution to overcome complex problems in smart lighting. A comprehensive review of improving user comfort is also presented, such as the methodology and taxonomy of activity recognition as a promising solution and user comfort metrics, including light utilization ratio, unmet comfort ratio, light to comfort ratio, power reduction rate, flickering perception, Kruithof's comfort curve, correlated color temperature, and relative mean square error. Finally, we discuss in-depth open issues and future challenges in increasing user comfort in smart lighting using activity recognition.

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Section: ) Internet Of Thingsmentioning

confidence: 99%

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

et al. 2022

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“…Also, specific sensor for detecting malfunctioning may be installed in order to reduce the maintenance costs. The same ideas may be also applied in indoor scenarios [46]. • Waste management: capacity sensors may be used to disseminate the status of each trash bin in the city, and such information may be used to optimize routing and scheduling of vehicles deputed to waste collection [14].…”

Section: Services For Urban Sustainabilitymentioning

confidence: 99%

Designing, Developing, and Facilitating Smart Cities

Angelakis¹,

Τράγος²,

Pöhls³

et al. 2017

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The Internet of Things (IoT) paradigm is expected to play a key role in the realization of Smart Cities characterized by heterogeneous service and stakeholders. The IoT ecosystem is further characterized by multiple available communication technologies and solutions with distinctive features in terms of network architectures, performance, cost, flexibility and availability. We provide here an overview of the main IoT-based communication technologies which can enable smart services for Smart Cities, further commenting on the main advantages, disadvantages and open challenges involved in applying each technology to the Smart City ecosystem.

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“…In a broader context, the relevance of the smart lighting control to reach the sustainability of smart cities is highlighted in [ 16 ], proposing an interoperable smart lighting solution based on Machine-to-Machine (M2M) protocols, such as CoAP over REST. From an abstract communication theoretic perspective, a hierarchical wireless network architecture of a smart lighting systems is proposed in [ 17 ], starting from IoT approaches and solutions, as well as on sensors and mobile technologies. A survey of networking solutions for smart lighting is provided in [ 18 ], including up-to-date sensing and networking technologies.…”

Section: Related Workmentioning

confidence: 99%

A Smart City Lighting Case Study on an OpenStack-Powered Infrastructure

Merlino

Bruneo

Distefano

et al. 2015

Sensors

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The adoption of embedded systems, mobile devices and other smart devices keeps rising globally, and the scope of their involvement broadens, for instance, in smart city-like scenarios. In light of this, a pressing need emerges to tame such complexity and reuse as much tooling as possible without resorting to vertical ad hoc solutions, while at the same time taking into account valid options with regard to infrastructure management and other more advanced functionalities. Existing solutions mainly focus on core mechanisms and do not allow one to scale by leveraging infrastructure or adapt to a variety of scenarios, especially if actuators are involved in the loop. A new, more flexible, cloud-based approach, able to provide device-focused workflows, is required. In this sense, a widely-used and competitive framework for infrastructure as a service, such as OpenStack, with its breadth in terms of feature coverage and expanded scope, looks to fit the bill, replacing current application-specific approaches with an innovative application-agnostic one. This work thus describes the rationale, efforts and results so far achieved for an integration of IoT paradigms and resource ecosystems with such a kind of cloud-oriented device-centric environment, by focusing on a smart city scenario, namely a park smart lighting example, and featuring data collection, data visualization, event detection and coordinated reaction, as example use cases of such integration.

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Enabling IoT empowered smart lighting solutions: A communication theoretic perspective

Cited by 12 publications

References 10 publications

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

Designing, Developing, and Facilitating Smart Cities

A Smart City Lighting Case Study on an OpenStack-Powered Infrastructure

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