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Smart city traffic optimization using IoD and IoT integration.

Aminu Yusuf1, Tarek R Sheltami2, Ashraf Mahmoud2

  • 1Computer Engineering Department, Interdisciplinary Research Center of Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. g202304010@kfupm.edu.sa.

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Summary
This summary is machine-generated.

This study integrates Internet of Things (IoT) and Internet of Drones (IoD) for smarter urban traffic management. The combined system significantly cuts travel delays and vehicle emissions, promoting sustainable mobility.

Keywords:
Drone-based traffic managementEmission reductionIntelligent transportation systemsIoTSustainable urban mobilityVehicle rerouting

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Area of Science:

  • Intelligent Transportation Systems
  • Wireless Communication Networks
  • Environmental Science

Background:

  • Urban traffic congestion leads to significant fuel waste and pollution.
  • Growing city populations exacerbate traffic issues, necessitating efficient management solutions.
  • Existing traffic management systems struggle with real-time data dissemination and coverage in all areas.

Purpose of the Study:

  • To propose and evaluate an integrated framework using Internet of Things (IoT) and Internet of Drones (IoD) for enhanced urban traffic management.
  • To improve traffic efficiency, reduce travel delays, and minimize vehicular emissions in urban environments.
  • To leverage drone technology for dynamic communication coverage extension in areas with sparse connectivity.

Main Methods:

  • Utilized Internet of Things (IoT) sensors for real-time traffic monitoring.
  • Employed Roadside Units (RSUs) for data processing and vehicle updates.
  • Implemented drones as mobile relay nodes to extend communication range, optimizing placement with Particle Swarm Optimization (PSO).
  • Conducted simulations using SUMO and TraCI with Python for communication protocols and adaptive rerouting.

Main Results:

  • The integrated IoT-IoD system demonstrated substantial reductions in travel delays and vehicular emissions.
  • In Dammam, emissions decreased by up to 40.99% and travel times by 32.05%.
  • In Doha, emissions decreased by up to 48.78% and travel times by 43.92%.

Conclusions:

  • Coordinated IoT-IoD systems effectively enhance urban traffic flow and operational efficiency.
  • The proposed framework significantly contributes to sustainable urban mobility and improved air quality.
  • Dynamic drone integration offers a scalable solution for real-time traffic information dissemination.