Sandi Ifan Maulana
Narotama University

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Determination Of Traffic Lights Duration By Identification Of Vehicle Numbers Using IoT Slamet Winardi; Sandi Ifan Maulana; Sri Wiwoho Mudjanarko; Benediktus Anindito
IJCONSIST JOURNALS Vol 1 No 1 (2019): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (966.367 KB) | DOI: 10.33005/ijconsist.v1i1.5

Abstract

Abstract— This research aimed to reduce the duration of time for quiet roads. Each motorized vehicle installed a WeMos chip as a client that contained each vehicle's license plate data. In the middle of the intersection, WeMos chip was installed as a traffic light controller to determine the duration and connect with cloud internet as a database server. It was installed at a distance of 50 meters as a scanner. It also detected the direction of arrival of motorized vehicles. Then, it would send the data to the cloud. It regulated the duration of the traffic light based on the data received and processed by the database server in each lane at the intersection. Determining the duration of traffic lights was based on sample time of motorcycles and cars, 1 second for motorcycles and 3 seconds for cars. This determination depended on the number of road junctions installed by this system. It was made standard, namely the total duration of time divided by the number of intersections. This time duration would run in a fixed order. If the number of vehicles on each track was as dense, it would skip certain paths. If one of the lanes did not have a vehicle, it would reduce the crowded of motorized vehicles from the other lanes because it would get a green light turn again without waiting for the time from the empty lane. In conclusion, it would be able to break down traffic density by giving priority time duration scale based on the calculation of the number of motorized vehicles by identifying the SSID of the vehicle license plate.