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IoT 18(13): e4

Research Article

Semantic Interoperable Traffic Management Framework for IoT Smart City Applications

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  • @ARTICLE{10.4108/eai.11-9-2018.155482,
        author={Sivadi Balakrishna and M. Thirumaran},
        title={Semantic Interoperable Traffic Management Framework for IoT Smart City Applications},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={4},
        number={13},
        publisher={EAI},
        journal_a={IOT},
        year={2018},
        month={1},
        keywords={Semantic Interoperability, Traffic Monitoring, Traffic detection, Smart City, IoT, Raspberry Pi, ThingSpeak, Cloud},
        doi={10.4108/eai.11-9-2018.155482}
    }
    
  • Sivadi Balakrishna
    M. Thirumaran
    Year: 2018
    Semantic Interoperable Traffic Management Framework for IoT Smart City Applications
    IOT
    EAI
    DOI: 10.4108/eai.11-9-2018.155482
Sivadi Balakrishna1,*, M. Thirumaran1
  • 1: Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry, India
*Contact email: balakrishna.sivadi@gmail.com

Abstract

Real-time traffic monitoring and controlling are one of the biggest problems in this present living world. So many researchers have dealt with and put their effort into this problem, as a result, several types of approaches have developed. Currently using traffic monitoring and alert systems are not up to the needs of smart city applications and more expensive. This paper proposes an Internet of Things (IoT) based Smart Real-Time Traffic Monitoring System to provide better service with low cost for Smart city applications using semantic annotations. The proposed framework contains two phases namely-traffic monitoring unit and traffic reduction unit. The first phase analyses semantic traffic to detect an emergency, the latter phase removes redundant semantic information for traffic reduction. Simulation results suggest that the framework is capable of accurate and early detection of an emergency as well as traffic reduction while keeping sufficient information to report the emergency.

Keywords
Semantic Interoperability, Traffic Monitoring, Traffic detection, Smart City, IoT, Raspberry Pi, ThingSpeak, Cloud
Received
2017-10-31
Accepted
2017-12-03
Published
2018-01-23
Publisher
EAI
http://dx.doi.org/10.4108/eai.11-9-2018.155482

Copyright © 2018 Sivadi Balakrishna et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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