The Conceptual of Pavement Management System Based on IoT, Big Data, and Data Mining in Indonesia

Thomas Setiabudi Aden, Hera Widyastuti*, Anak Agung Gde Kartika

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


The country's economic development and people's lives require reliable transportation and logistics services. Therefore, road maintenance policies and techniques must be more comprehensive to ensure transportation infrastructure operations' efficiency. The inefficiency of road maintenance, among others, is due to the failure to identify and predict the level of damage that can cause fundamental data anomalies. Therefore, the current scientific development of road maintenance must be able to take advantage of the convenience of technology. Widespread technology implementation on the Internet of Think (IoT), big data, and data mining (DM) can be a solution to developing a better pavement management system. However, implementing these technologies is challenging due to the weak conception and availability of currently available resources. This paper offers a pavement system management implementation concept that can be developed in Indonesia to improve the existing system. The study results show that IoT, big data, and DM are believed to support a more intelligent and comprehensive pavement management system. The concept offered consists of three main things: identification of damage and 3D pavement modeling, data analysis, decision support systems, and collaboration of intelligent solutions in implementing maintenance in the field. This paper is equipped with an illustration of the concept of road maintenance based on IoT, big data, and DM, which can be implemented intelligently and simply in Indonesia.

Original languageEnglish
Article number01001
JournalE3S Web of Conferences
Publication statusPublished - 15 Apr 2024
Event10th International Conference on Engineering, Technology, and Industrial Application, ICETIA 2023 - Surakarta, Indonesia
Duration: 7 Dec 20238 Dec 2023


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