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LoRa based architecture for smart town traffic management system

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Abstract

While traffic congestion has been pointed out as everyday driving stress, few attempts are specialized in traffic management by using current IoT technology. In order to help alleviate traffic stress from drivers, this article proposes a cross-layer LoRa architecture and a machine-learning algorithm for smart town’s traffic management systems. LoRa is selected since it has strengths in range and power when compared to other wireless communication technologies. We introduce the cross-layer LoRa architecture, which is devised to facilitate its cognitive analysis. By dynamically allocating network and information resources, it complements the limitations of the standard LoRa protocol. We also have designed the logistic regression algorithm-which runs above its cognitive engine. The proposed algorithm outputs traffic coefficients based on density and travel time. This algorithm has achieved 97% of accuracy in the simulation. With further research, we believe the proposed system could be an excellent solution for smart traffic management.

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Acknowledgements

Conceptualization, formal analysis and investigation, validation: Seung Byum Seo; methodology, writing-original draft preparation, formal analysis: Pamul Yadav; writing—review and editing, supervision, project administration, funding acquisition: Dhananjay Singh. All authors have read and agreed to the published version of the manuscript.

Funding

This research work was supported by VESTELLA and Hankuk University of Foreign Studies research fund.

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Author notes

  1. Seung Byum Seo and Pamul Yadav contributed equally to this work.

Authors and Affiliations

  1. ReSENSE Lab, Department of Electronics Engineering, Hankuk University of Foreign Studies, Global Campus, Seoul, Republic of Korea

    Seung Byum Seo & Dhananjay Singh

  2. Department of Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

    Pamul Yadav

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  1. Seung Byum Seo
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  2. Pamul Yadav
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  3. Dhananjay Singh
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Correspondence to Dhananjay Singh.

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Seo, S.B., Yadav, P. & Singh, D. LoRa based architecture for smart town traffic management system. Multimed Tools Appl 81, 26593–26608 (2022). https://doi.org/10.1007/s11042-020-10091-5

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  • DOI: https://doi.org/10.1007/s11042-020-10091-5

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