Idle Vehicle Detection and Traffic Symbol Analysis using Artificial Intelligence and IoT

Arun Kumar K; Ashwin D; Surendar M; Manju Parkavi N; Banumathi P; Rajagopal T.K.P.

doi:10.34256/irjmt19210

Articles

Home / Archives / Volume 1, Issue 2, Year 2019 /

DOI: 10.34256/irjmt19210

Idle Vehicle Detection and Traffic Symbol Analysis using Artificial Intelligence and IoT

Arun Kumar K⁺⁻
Ashwin D⁺⁻
Surendar M⁺⁻
Manju Parkavi N⁺⁻
Banumathi P⁺⁻
Rajagopal T.K.P.⁺⁻

UG Scholar, Department of Computer science & Engg, Kathir College Of Engg, Coimbatore, TN, India

UG Scholar, Department of Computer science & Engg, Kathir College Of Engg, Coimbatore, TN, India 2Professor, Department of Computer Science & Engg, Kathir College Of Engg, Coimbatore, TN, India

UG Scholar, Department of Computer science & Engg, Kathir College Of Engg, Coimbatore, TN, India

Professor, Department of Computer Science & Engg, Kathir College Of Engg, Coimbatore, TN, India

Associate Professor, Department of Computer Science & Engg, Kathir College Of Engg, Coimbatore, TN, India

Dimensions

Plum Analytics

Abstract

The emerging development in smart vehicles has improved transportation seamlessly. This paper deals with incorporating the modern technologies like Artificial Intelligence and Internet of Things(IoT) with the traditional transportation system. It states how AI algorithms can be integrated with IoT powered vehicles to manage and avoid crashing with idle vehicles on a speedway and assists for safer driving using the traffic symbol analysis to reduce accidents. Several communication standards for data transmission between the vehicle and control system has been stated. It also provides additional features like emergency or assistance for vehicles in speedway. It uses complex learning and analysis algorithms to improve the efficiency of driving and reduce rear-end collisions. This paper hence gives a comprehensive survey of the enabling technologies, protocols, and architecture for IoT powered transport.

Keywords

Internet of things, Wireless Sensor Network(WSN), IR sensor, Wireless data transmission, Radio frequency Identification, traffic symbol analysis, idle vehicle,

Downloads

Download data is not yet available.

References

Zanella, N. Bui, A. Castellani, L. Vangelista, and M. Zorzi, ‘‘InternetofThingsforsmartcities, IEEEInternetThingsJ., 2014, vol.1,no.1, pp. 22–32.
G. Dimitrakopoulos and P. Demestichas, Intelligent transportation systems, IEEE Veh. Technol. Mag.,2010, vol. 5, no. 1, pp. 77–84.
F.-Y. Wang, ‘‘Parallel control and management for intelligent transportation systems: Concepts, architectures, and applications,’IEEE Trans. Intell. Transp. Syst., 2010, vol. 11, no. 3, pp. 630–638,
J. Zhang, F.-Y. Wang, K. Wang, W.-H. Lin, X. Xu, and C. Chen, Datadriven intelligent transportation systems: A survey, IEEE Trans. Intell. Transp. Syst., 2011, vol. 12, no. 4, pp. 1624–1639.
Enterprise Ireland, Intelligent transport system A directory of irish resources, ’’inProc.9thEur.Intell.TransportSyst.Congr.,Dublin, Ireland, 2013, pp. 1–44.
F.-Y. Wang, C. Herget, and D. Zeng, Developing and improving transportation systems: The structure and operation of IEEE Intelligent Transportation Systems Society, (Guest Editorial), IEEE Trans. Intell. Transport. Syst., 2005vol. 6, no. 3, pp. 261–264.
F.-Y. Wang, Agent-Based Control for Networked Traffic Management Systems, IEEE Intelligent Systems, , 2005, vol. 20, no. 5, pp. 92–96.
F.-Y. Wang and S. Tang, Artificial Societies for Integrated and Sustainable Development of Metropolitan Systems, IEEE Intelligent Systems, 2004, vol. 19, no. 4, pp. 82–87.