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IOT based Smart Traffic Light Control System

  • Anna Merine George
  • , V. I. George
  • , Mary Ann George

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Traffic Congestion and traffic monitoring is one of the important problems all over the world. This work uses IOT and Adaptive Neuro Fuzzy Inference System (ANFIS) to improve traffic conditions. An ANFIS traffic light controller with inputs as waiting time and vehicle density is developed using MATLAB SIMULINK environment. A camera is used to capture the traffic scenes and this image is transferred to the cloud using Arduino UNO and ThingSpeak Platform. The image is then analyzed in the server using ANFIS controller and appropriate control signals are sent to the traffic signals.

    Original languageEnglish
    Title of host publication2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages148-151
    Number of pages4
    ISBN (Electronic)9781538607961
    DOIs
    Publication statusPublished - 12-12-2018
    Event2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018 - Kannur,Kerala, India
    Duration: 23-03-201824-03-2018

    Publication series

    Name2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018

    Conference

    Conference2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018
    Country/TerritoryIndia
    CityKannur,Kerala
    Period23-03-1824-03-18

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure

    All Science Journal Classification (ASJC) codes

    • Artificial Intelligence
    • Computer Science Applications
    • Signal Processing
    • Energy Engineering and Power Technology
    • Control and Optimization
    • Computer Networks and Communications

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