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DOI: 10.14569/IJACSA.2019.0101244
PDF

Predictive Control for Distributed Smart Street Light Network

Author 1: Pei Zhen Lee
Author 2: Sei Ping Lau
Author 3: Chong Eng Tan

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.

  • Abstract and Keywords
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Abstract: With the advent of smart city that embedded with smart technology, namely, smart streetlight, in urban development, the quality of living for citizens has been vastly improved. TALiSMaN is one of the promising smart streetlight schemes to date, however, it possesses certain limitation that led to network congestion and packet dropped during peak road traffic periods. Traffic prediction is vital in network management, especially for real-time decision-making and latency-sensitive application. With that in mind, this paper analyses three real-time short-term traffic prediction models, specifically simple moving average, exponential moving average and weighted moving average to be embedded onto TALiSMaN, that aim to ease network congestion. Additionally, the paper proposes traffic categorisation and packet propagation control mechanism that uses historical road traffic data to manage the network from overload. In this paper, we evaluate the performance of these models with TALiSMaN in simulated environment and compare them with TALiSMaN without traffic prediction model. Overall, weighted moving average showed promising results in reducing the packet dropped while capable of maintaining the usefulness of the streetlight when compared to TALiSMaN scheme, especially during rush hour.

Keywords: Traffic prediction; adaptive street lighting; smart cities; energy efficient; network congestion

Pei Zhen Lee, Sei Ping Lau and Chong Eng Tan, “Predictive Control for Distributed Smart Street Light Network” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101244

@article{Lee2019,
title = {Predictive Control for Distributed Smart Street Light Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101244},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101244},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Pei Zhen Lee and Sei Ping Lau and Chong Eng Tan}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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