Smart Survey Model of Average Daily Traffic (ADT) for Pavement Planning and Monitoring Arthur Daniel Limantara (1*), Tjahjaning Tingastuti Surjosuseno (1), Bambang Subiyanto (2), Fauzie Nursandah (2), Sri Wiwoho Mudjanarko (3), Muhammad Ikhsan Setiawan (3), Nawir Rasidi (4)
1) Department of Informatics, Cahaya Surya College of Technology, Perintis Kemerdekaan 36A, Kediri, Indonesia
* arthur.limantara[at]gmail.com
2) Department of Civil Engineering, Kadiri University, Selomangleng 1, Kediri, Indonesia
3) Department of Civil Engineering, Narotama University, Arief Rachman Hakim 51, Surabaya, Indonesia
4) Department of Civil Engineering, State Polytechnic of Malang, Soekarno-Hatta No. 9, Malang, Indonesia
Abstract
Daily traffic volume surveys for manual pavement planning and supervision require labor, time, and are not cheap. Besides that, the accuracy and speed of obtaining the data are not timely. This study aims to obtain a smart survey model that will function to obtain daily traffic volume data automatically and in real-time, as well as processing it. The methodology used modeling the survey process by utilizing smart devices, microcontrollers, sensors, and the internet of things, as well as cloud programming and client servers. The survey process model can be divided into 2 parts, namely part 1 which is in charge of collecting vehicle data, and part 2 to collect the axle load of each vehicle, then the data will be sent via the access point to the cloud, cloud data is taken by the data processing center server for data processing. The model produces traffic volume data information with speeds of up to 67.4 Mbps, data accuracy of 98%, and real-time data processing results can be used as monitoring of pavement age.
Keywords: Traffic Volume Survey, Smart Survey Modeling, Internet of Things (IoT), Pavement Planning, and Monitoring.
