Survey on Real-Time Intelligent Traffic Light Monitoring And Control System Using Data Mining And WSN

DIPTI M JAISINGHANI; A.M.BONGALE

Survey on Real-Time Intelligent Traffic Light Monitoring And Control System Using Data Mining And WSN

Authors: DIPTI M JAISINGHANI, A.M.BONGALE

Unique Paper ID: 142837
Volume: 2
Issue: 7
PageNo: 268-272

Keywords: Wireless sensor Networks (WSN) Iterative Dichotomiser 3 (ID3) Analog to Digital convertor (ADC).

Abstract:
This paper, presents a Real-time Intelligent traffic light monitoring and control system to predict traffic congestion using Iterative Dichotomiser 3 (ID3) data mining and Wireless Sensor Network (WSN). This system not only measures the current vehicle count and different climatic condition such as temperature, gas and light through wireless sensor nodes but also we predict the possibility of traffic congestion for particular road range by using CSE5230 ID3 Data mining algorithm on system database. Systems approach is to design a delay timer for traffic signal light control, which uses historical collected data and automatically identifies the delay time for traffic signal light. 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. System uses micro controller Bluetooth and an android device for connecting server to different sensors like IR sensor, temperature sensor, light sensor and gas sensor with the help of RS-232 and ADC. Database stores the log files containing information about history of climatic condition, the count of vehicle and details of traffic congestion. With the help of which system intelligently study the future control of delay timer for Red, Green and Orange, traffic signal lights.

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Cite This Article

ISSN: 2349-6002
Volume: 2
Issue: 7
PageNo: 268-272

Survey on Real-Time Intelligent Traffic Light Monitoring And Control System Using Data Mining And WSN

Available:https://ijirt.org/Article?manuscript=142837

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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