IJERT-EMS
IJERT-EMS

Real-Time Intelligent Traffic Light Monitoring and Control System to Predict Traffic Congestion Using Data Mining and WSN


Real-Time Intelligent Traffic Light Monitoring and Control System to Predict Traffic Congestion Using Data Mining and WSN
Authors : Dipti Jaisinghani, Prof. A. M. Bongale
Publication Date: 03-12-2015

Authors

Author(s):  Dipti Jaisinghani, Prof. A. M. Bongale

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Volume. 4 - Issue. 12 , December - 2015

e-ISSN:   2278-0181

 DOI:  http://dx.doi.org/10.17577/IJERTV4IS120040

Abstract

Traffic monitoring and control are becoming more and more important as number of vehicles and traffic jams grow. Strategically placed video cameras are predominantly used to perform this task by visual means. To improve traffic monitoring and control this paper presents Realtime Intelligent traffic light monitoring and control automated system, to predict traffic congestion using Iterative Dichotomiser 3 (ID3) data mining algorithm and Wireless Sensor Network (WSN). At a junction, infrared sensor is used to count the number of vehicles on each road and send the report to Traffic Monitoring and Control (TMCM) for traffic estimation[1]. Along with infrared sensors, this system consists of light, temperature and gas sensors to measure day-night, temperature and pollution at the junction. Traffic and climatic data obtained from these sensors are aggregated in TMCM to form data logs stored in database, which is further used to extract traffic information as per system requirement. TMCM consist of micro controller (AVR ATmega32), Bluetooth (HC- 05) and an android device for connecting server to different sensors like IR sensor, temperature sensor(LM35), light sensor and gas sensor with the help of MAX-232 and ADC. Proposed system not only measures the traffic flow and different climatic scenarios through wireless sensor nodes but also predicts the possibility of traffic congestion for relevant junction by using CSE5230 ID3 Data mining algorithm on collected database. Using historically collected data from database system intelligently decides the delay timer of Red-Green-Orange traffic signal light. This delay timer is automatically set based on the flow of traffic on each road of associated junction and data logs maintained in database. Traffic congestion information and climatic scenario are employed for early warning with the use of server to android-based mobile phones or smart phones connected via a web service.

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