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Broken Road Detection Methods Comparison: A Literature Survey Indra Yustiana; Somantri; Dudih Gustian; Anggy Pradifta Junfithrana; Satish Kumar Damodar
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 5 No. 2 (2022): November 2022
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/ijeat.v5i2.75

Abstract

Roads are infrastructure built to facilitate regional development. Good road conditions will certainly provide a sense of comfort for every vehicle that will pass through it. For that, care and attention to road conditions needs to be done. The occurrence of damage to the road will hinder the development process. Currently, detection of damaged roads is still done manually using human resource. It makes the detection process take quite a lot of time to determine how bad the damage is. So there needs a way to help improve time efficiency and accuracy in detecting damaged roads. One of them is by utilizing machine learning technology. In this paper, we will discuss what methodology can be use and their comparisons to be able to use appropriate and effective methodologies to detect cases of damaged roads