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Cited by 73Smart Cities and TechnologiesIoT and Edge/Fog ComputingWireless Sensor Networks and IoT

The DOI matches its Crossref record.

An Implementation of High Efficient Smart Street Light Management System for Smart City

Open access
Yang, Yu-Sheng, Lee, Shih-Hsiung, Chen, Guan-Sheng, Yang, Chu-Sing, Huang, Yueh-Min, Hou, Ting-Wei·2020·IEEE Access
DOI 10.1109/access.2020.2975708
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Abstract

Street light are among the most common infrastructure in cities. Street lights and sensors can be combined to generate an interface of data collection. The analysis of massive data serves as an integral element of a smart city. This paper proposes a highly efficient system for the configuration, deployment, and management of smart street lights. The features of fast deployment and high scalability of the container-based system management result in virtual deployment. Additionally, for database design, NoSQL and in-memory databases are integrated to realize flexible data management. In terms of data transmission, this paper designs an asymmetric key and an SSH encrypted tunnel. Moreover, when all the services are connected, it conducts legitimacy validation via a token. Therefore, this system can help meet the demands for data throughput, low-latency, configuration, and realization of a smart city. It boasts high efficiency and security. Besides, it offers a flexible data storage and management service to facilitate the massive data processing of a smart city. With respect to experiments, this paper designs a street lighting simulation system with edge computing devices (consisting of a micro-controller, a sensor, and an IP camera) and a street lighting function. The system collects real-time sensed environmental data, enables live streaming of images, and offers an API for historical data query. This paper utilizes container-based virtualization to deploy all edge computing devices on the server and validates the feasibility of simultaneous operation of multiple container-based services on edge computing devices. This system has high commercial value.

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Metadata

Authors
Yang, Y.-S., Lee, S.-H., Chen, G.-S., Yang, C.-S., Huang, Y.-M., & Hou, T.-W.
Affiliations
  • National Kaohsiung University of Science and Technology (TW)
  • National Cheng Kung University (TW)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2020
Volume
8
Pages
38568-38585
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2020.2975708
OpenAlex
W3008377868
Cited by
73
References
0
Citations by year
2026: 11 · 2025: 11 · 2024: 13 · 2023: 10 · 2022: 15 · 2021: 10 · 2020: 3
FWCI
4.89
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Access (publishedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Urban Studies › Smart Cities and Technologies
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Engineering › Control and Systems Engineering › Wireless Sensor Networks and IoT
Keywords
smart street lighting, smart cities, container-based virtualization, edge computing, NoSQL databases, in-memory databases, public-key cryptography, token-based authentication, big data management, IP cameras, historical data query

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