Depok, W Java (ANTARA) – A University of Indonesia (UI) researcher has developed an artificial intelligence-based method to detect and measure road surface depressions, potentially making infrastructure inspections faster, more objective and more accurate.
Agus Mulyanto of the university’s Faculty of Engineering combined deep learning, three-dimensional geometric analysis and binocular stereo vision cameras to automatically identify and measure road surface deterioration.
In his dissertation, titled “Development of a Road Depression Inspection Method Based on Deep Learning and Three-Dimensional Geometric Analysis Using a Binocular Stereo Vision Camera,” Agus detailed the integrated approach.
“I hope this research contributes to road inspection technology using artificial intelligence and three-dimensional analysis, supporting more effective infrastructure maintenance and safer, more sustainable transportation systems,” Agus said here Tuesday.
The system can capture depth information from road surfaces, allowing it to identify damage more accurately, according to the researcher.
Binocular stereo vision cameras also allow the system to reconstruct road surfaces in three dimensions, while integrating geometric characteristics with AI provides a more comprehensive assessment.
The approach improves the objectivity of inspection results while reducing potential errors commonly associated with conventional road assessments, according to the research findings.
The study found that combining AI with three-dimensional analysis has significant potential to transform road infrastructure maintenance systems in Indonesia.
The technology could help policymakers, road operators and transportation companies monitor road conditions more quickly, identify damage sooner and prioritize maintenance based on available data.
The research also underscores the University of Indonesia’s efforts to support academic innovation and apply digital technologies to challenges facing national development.
The AI-based monitoring system is intended not only to improve inspection efficiency but also to support safer, more reliable and sustainable transport infrastructure while accelerating digital transformation across Indonesia’s transportation sector.
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Translator: Feru L, Rahmad Nasution
Editor: Primayanti
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