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Secure Design and Implementation of Smart Traffic Light Management System

  • Conference paper
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Cryptology and Network Security with Machine Learning (ICCNSML 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 918))

  • 78 Accesses

Abstract

By identifying areas of heavy congestion, smart traffic management systems can then implement measures to alleviate that problem. In order to accomplish this, it analyzes and synchronizes data from sensors in real-time. The input data are used to determine when the traffic signal blinks due to congestion. This method has the potential to lessen air pollution and make roads safer for everyone. In this research, we offer a smart technique for accurate traffic estimate prediction using random forest. In the majority of instances, the approximate traffic estimate is better than the shortest route with respect to overall travel time and fuel cost. Based on our findings, we were able to decrease the average waiting time of vehicles while still accurately forecasting traffic.

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Author information

Authors and Affiliations

  1. VIT Bhopal University, Bhopal, 466114, India

    Anju Shukla & Akshat Anand

  2. Pranveer Singh Institute of Technology, Kanpur, 209305, India

    Varun Shukla

  3. Babasaheb Bhimrao Ambedkar University, Lucknow, 226025, India

    Shishir Kumar

Authors
  1. Anju Shukla
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  2. Varun Shukla
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  3. Shishir Kumar
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  4. Akshat Anand
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Corresponding author

Correspondence to Anju Shukla .

Editor information

Editors and Affiliations

  1. Department of Mathematics, Pranveer Singh Institute of Technology, Kanpur, India

    Atul Chaturvedi

  2. Department of Mathematics, Indian Institute of Technology Jammu, Jammu, India

    Sartaj Ul Hasan

  3. Applied Statistics Unit, Indian Statistical Institute, Kolkata, India

    Bimal Kumar Roy

  4. Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel

    Boaz Tsaban

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Shukla, A., Shukla, V., Kumar, S., Anand, A. (2024). Secure Design and Implementation of Smart Traffic Light Management System. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_5

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  • DOI: https://doi.org/10.1007/978-981-97-0641-9_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0640-2

  • Online ISBN: 978-981-97-0641-9

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