Intelligent Mobility Solutions Utilizing Internet of Things and Artificial Intelligence for Sustainable Smart Transportation Networks

Murali Malempati; P. Balakrishnan; A. Naveenkumar; R. Senthil Kumar; Om Prakash Yadav; Thomas Koilraj

doi:10.2991/978-94-6463-718-2_66

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Intelligent Mobility Solutions Utilizing Internet of Things and Artificial Intelligence for Sustainable Smart Transportation Networks

Authors

Murali Malempati¹, P. Balakrishnan²^{, *}, A. Naveenkumar³, R. Senthil Kumar⁴, Om Prakash Yadav⁵, Thomas Koilraj⁶

¹Senior Software Engineer, Department of Electrical and Electronics Engineering, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India

²Professor, Department of Electrical and Electronics Engineering, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India

³Assistant Professor, Department of IT, Sona College of Technology, Salem, 636005, Tamil Nadu, India

⁴Assistant Professor, Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Chengalpattu District, Kattankulathur, Chennai, 603203, Tamil Nadu, India

⁵Associate Professor, School of Computer Science & Engineering, Lovely Professional University, Punjab, India

⁶Assistant Professor, Department of Mechanical Engineering, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India

^*Corresponding author. Email: balakrishnanp@jjcet.ac.in

Corresponding Author

P. Balakrishnan

Available Online 23 May 2025.

DOI: 10.2991/978-94-6463-718-2_66 How to use a DOI?
Keywords: Intelligent Mobility; Smart Transportation Networks; Internet of Things (IoT); Artificial Intelligence (AI); Machine Learning for IoT; Cybersecurity in Smart Mobility; Sustainable Transportation; Vehicular Fog Computing; AI-driven Decision Making
Abstract: The rapid urbanization and increasing demand for efficient transportation systems have necessitated the integration of Internet of Things (IoT) and Artificial Intelligence (AI) into modern smart mobility solutions. While existing research has explored these technologies independently, significant gaps remain in their practical scalability, security, sustainability, and real-time decision-making. This study proposes a holistic framework that combines IoT-driven data collection with AI-based analytics to enhance transportation networks’ efficiency, safety, and environmental sustainability. Unlike previous works that focus on theoretical AI applications, this research emphasizes real-world implementation, cybersecurity measures, energy-efficient vehicular fog computing, and machine learning optimization for IoT data analytics. Additionally, we introduce a privacy-preserving AI model for smart transportation, ensuring secure and ethical decision-making. Through comparative analysis, simulation-based validation, and case studies, this paper provides a scalable, secure, and sustainable approach to intelligent mobility solutions. The results demonstrate improved traffic congestion prediction, route optimization, real-time security threat detection, and enhanced decision-making frameworks. This research aims to bridge the gap between theoretical AI models and their large-scale deployment in smart transportation networks, ultimately fostering a more resilient and sustainable urban mobility ecosystem.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series: Advances in Computer Science Research
Publication Date: 23 May 2025
ISBN: 978-94-6463-718-2
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-718-2_66 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Murali Malempati
AU  - P. Balakrishnan
AU  - A. Naveenkumar
AU  - R. Senthil Kumar
AU  - Om Prakash Yadav
AU  - Thomas Koilraj
PY  - 2025
DA  - 2025/05/23
TI  - Intelligent Mobility Solutions Utilizing Internet of Things and Artificial Intelligence for Sustainable Smart Transportation Networks
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 767
EP  - 778
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_66
DO  - 10.2991/978-94-6463-718-2_66
ID  - Malempati2025
ER  -

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