IOT based Smart Traffic Light Control System

Anna Merine George; V. I. George; Mary Ann George

doi:10.1109/ICCPCCT.2018.8574285

IOT based Smart Traffic Light Control System

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

Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Citations (Scopus)

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 language	English
Title of host publication	2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	148-151
Number of pages	4
ISBN (Electronic)	9781538607961
DOIs	https://doi.org/10.1109/ICCPCCT.2018.8574285
Publication status	Published - 12-12-2018
Event	2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018 - Kannur,Kerala, India Duration: 23-03-2018 → 24-03-2018

Conference

Conference	2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018
Country/Territory	India
City	Kannur,Kerala
Period	23-03-18 → 24-03-18

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

UN SDGs

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

Access to Document

10.1109/ICCPCCT.2018.8574285

Cite this

@inproceedings{05396d86f40f4b6ebce0964f05fe3888,

title = "IOT based Smart Traffic Light Control System",

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.",

author = "George, {Anna Merine} and George, {V. I.} and George, {Mary Ann}",

year = "2018",

month = dec,

day = "12",

doi = "10.1109/ICCPCCT.2018.8574285",

language = "English",

pages = "148--151",

booktitle = "2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018 ; Conference date: 23-03-2018 Through 24-03-2018",

}

George, AM, George, VI & George, MA 2018, IOT based Smart Traffic Light Control System. in 2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018., 8574285, Institute of Electrical and Electronics Engineers Inc., pp. 148-151, 2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018, Kannur,Kerala, India, 23-03-18. https://doi.org/10.1109/ICCPCCT.2018.8574285

IOT based Smart Traffic Light Control System. / George, Anna Merine; George, V. I.; George, Mary Ann.
2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 148-151 8574285.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - IOT based Smart Traffic Light Control System

AU - George, Anna Merine

AU - George, V. I.

AU - George, Mary Ann

PY - 2018/12/12

Y1 - 2018/12/12

N2 - 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.

AB - 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.

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DO - 10.1109/ICCPCCT.2018.8574285

M3 - Conference contribution

AN - SCOPUS:85060024823

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EP - 151

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 International Conference on Control, Power, Communication and Computing Technologies, ICCPCCT 2018

Y2 - 23 March 2018 through 24 March 2018

ER -

IOT based Smart Traffic Light Control System

Abstract

Conference

All Science Journal Classification (ASJC) codes

UN SDGs

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