AI tool developed in Indonesia detects unreported road damage, revealing hidden infrastructure issues and changing how roads are monitored.
Road infrastructure problems in Indonesia have long been difficult to fully map, with many damaged roads going unreported and unnoticed. Now, a breakthrough developed by an ITS researcher introduces an AI-based system capable of detecting and identifying road damage more accurately and efficiently.
This innovation is reshaping infrastructure monitoring and transforming maintenance strategies as well as public safety responses across the country. Stay tuned Techniquit.
Growing Problem Of Unrecorded Road Damage In Indonesia
Road infrastructure in Indonesia continues to face a major challenge: many damaged roads are not properly recorded in official data systems. This creates delays in maintenance and increases risks for road users, especially in urban and rural areas with high traffic intensity.
According to research highlighted by an ITS academic, traditional road inspection methods still rely heavily on manual surveys. These methods are not only time-consuming but also often fail to capture real-time road conditions accurately.
As a result, many road defects such as potholes and surface cracks remain undetected until they cause serious disruption. This gap in data collection has encouraged researchers to develop smarter, automated solutions.
ITS Doctor Develops AI-Based Road Detection System
A doctor from the Institut Teknologi Sepuluh Nopember (ITS) has developed an innovative artificial intelligence (AI) system designed to detect unreported road damage. The system uses advanced machine learning techniques to identify road defects more efficiently.
The innovation was created in response to the slow and costly process of conventional road surveys. The researcher emphasized that faster detection is crucial to improving infrastructure maintenance and ensuring road safety.
By integrating AI into road monitoring, the system can automatically analyze visual data from roads and classify different types of damage, making the process more accurate and efficient compared to manual methods.
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How The AI Technology Works In Road Monitoring
The system developed by the ITS researcher uses image and video data collected from road surfaces through camera sensors installed on vehicles. This data is then processed using deep learning algorithms.
One of the core technologies used is a Convolutional Neural Network (CNN), which is capable of recognizing patterns such as potholes, cracks, and surface deformation. The AI model processes this information in real time.
The processed data is then transmitted to an edge computing device, allowing faster analysis directly in the field without relying heavily on centralized systems. This improves both speed and efficiency in detecting road damage.
Benefits For Infrastructure And Public Safety
The implementation of AI-based road detection offers significant benefits for infrastructure management in Indonesia. One of the main advantages is the ability to reduce delays in identifying damaged roads.
With faster detection, authorities can respond more quickly to repair needs, reducing the risk of accidents caused by poor road conditions. This also helps improve overall transportation safety for the public.
In addition, the system can help optimize maintenance budgets by ensuring that repairs are carried out based on accurate and timely data, rather than delayed manual reporting.
Future Potential And Smart Infrastructure Development
Researchers believe that AI-based road detection systems can become an important part of future smart city infrastructure. By integrating this technology with national transportation systems, road monitoring can become more automated and reliable.
The innovation also supports the development of digital infrastructure ecosystems where data plays a central role in decision-making. This aligns with global trends in smart mobility and urban planning.
In the future, such AI systems could be expanded to cover wider areas. Helping governments build more efficient, safe, and sustainable road networks across Indonesia.
Image Source:
- First Image from detik.com
- Second Image from binamarga.pu.go.id
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