The Role of Blockchain, AI and IoT for Smart Road Traffic Management System
Abstract
Nowadays vehicles are increasing on the road. Due to this, it is a challenge for society to manage traffic jams and road accidents all over the world. Artificial Intelligence (AI) such as Machine Learning (ML) algorithms are very helpful to improve the performance of the overall road safety management system. AI is used for many real-world applications to make any system be a smart system. The Smart Road Traffic Management System (SRTMS) easily recognizes the influence occurs for random changes on road safety. The SRTMS detects the unsafe driving patterns as well as convey the information to the respective authorities. The Internet of Things (IoT) is a boon technology to observe human activities in real-time. IoT devices or nodes are composed of sensors that are commonly utilized to identify and reply to electrical and other signals. Currently, Blockchain (BC) is the most trending technology to automate transactions, which means sharing or exchange of information between the IoT devices or nodes. BC technology facilitates for sharing of information on the network is decentralized, secure, persistent, anonymity, suitability and trustworthy manner. With consensus algorithms and smart contracts, Blockchain holds to manage communication among nodes without the involvement of a third-party or intermediary body. Simultaneously, AI has the ability to offer intelligent and decision-making machines similar to human beings' minds. This paper proposes the SRTMS model for solving the roa…
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This helps in optimizing traffic flow and reducing congestion.
“This helps in optimizing traffic flow and reducing congestion [80] .”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [80]
AI, ML, and DL techniques are used to monitor and analyze traffic patterns.
“Traffic Management: AI, ML, and DL techniques are used to monitor and analyze traffic patterns.”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [80]
Cites
Towards blockchain-based intelligent transportation systems
Yuan, Y., & Wang, F.-Y. (2016) · 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2016.7795984 · Cited by 671 · see citing works
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Soori, M., Arezoo, B., & Dastres, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.001 · Cited by 1,131 · see citing works
- Authors
- Sharma, A., Awasthi, Y., & Kumar, S.
- Affiliations
- Lebanese French University (IQ)
- Amity School of Engineering and Technology Amity, University,Noida,UP,India
- Venue
- 2020 IEEE India Council International Subsections Conference (INDISCON)
- Publisher
- IEEE
- Published
- 2020-10
- Pages
- 289-296
- OpenAlex
- W3127607133
- Cited by
- 69
- References
- 1
- Citations by year
- 2026: 5 · 2025: 23 · 2024: 16 · 2023: 12 · 2022: 10 · 2021: 2 · 2020: 1
- FWCI
- 4.67
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE India Council International Subsections Conference (INDISCON) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Engineering › Mechanical Engineering › IoT and GPS-based Vehicle Safety Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- blockchain, artificial intelligence, Internet of Things, road safety, traffic jam detection, traffic accident detection, smart contracts, consensus algorithms, decentralized information sharing
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