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A Novel Study on IoT and Machine Learning-Based Transportation

A Novel Study on IoT and Machine Learning-Based Transportation

Vibhor Sharma, Deepak Srivastava, Lokesh Kumar, Mohit Payal
Copyright: © 2024 |Pages: 28
ISBN13: 9798369352717|ISBN13 Softcover: 9798369352724|EISBN13: 9798369352731
DOI: 10.4018/979-8-3693-5271-7.ch001
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MLA

Sharma, Vibhor, et al. "A Novel Study on IoT and Machine Learning-Based Transportation." Machine Learning Techniques and Industry Applications, edited by Pramod Kumar Srivastava and Ashok Kumar Yadav, IGI Global, 2024, pp. 1-28. https://doi.org/10.4018/979-8-3693-5271-7.ch001

APA

Sharma, V., Srivastava, D., Kumar, L., & Payal, M. (2024). A Novel Study on IoT and Machine Learning-Based Transportation. In P. Srivastava & A. Yadav (Eds.), Machine Learning Techniques and Industry Applications (pp. 1-28). IGI Global. https://doi.org/10.4018/979-8-3693-5271-7.ch001

Chicago

Sharma, Vibhor, et al. "A Novel Study on IoT and Machine Learning-Based Transportation." In Machine Learning Techniques and Industry Applications, edited by Pramod Kumar Srivastava and Ashok Kumar Yadav, 1-28. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-5271-7.ch001

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Abstract

Smarter apps and connected devices are now possible because of the proliferation of IoT, which has greatly improved the quality of life in today's urban centers. ML and IoT approaches have been employed in the study of smart transportation, which has attracted a large number of researchers. Smart transportation is viewed as a catch-all word that encompasses a wide range of topics, including optimization of route, parking, street lighting, accident detection, abnormalities on the road, and other infrastructure-related issues. The purpose of this chapter is to examine the state of machine learning (ML) and internet of things (IoT) applications for smart city transport in order to better comprehend recent advances in these fields and to spot any holes in coverage. From the existing publications it's clear that ML may be underrepresented in smart lighting and smart parking systems. Additionally, researchers' favorite applications in terms of transportation system's intelligence include optimization of route, smart parking management, and accident/collision detection.

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