KBRN, Jakarta: The Indonesian National Research and Innovation Agency (BRIN), through its Smart Mechatronics Research Center under the Electronics and Informatics Research Organization, is intensifying research on artificial intelligence (AI) and autonomous vehicles, with a particular focus on railway infrastructure diagnostics and healthcare applications. 

The initiative aims to enhance transportation safety and improve the quality of medical services.

Yanuandri Putrasari, Head of the Smart Mechatronics Research Center, noted that AI-driven autonomous technology is advancing rapidly and can be applied across multiple sectors. 

“Autonomous vehicles are not limited to public road transport; they can also be utilized in railway systems and medical services. We hope this webinar will expand networks and collaborations in autonomous vehicle research,” he said at the opening of a recent webinar, as quoted on BRIN's official website.

Mohammad Abu Jami’in from the Surabaya State Shipping Polytechnic presented research on computer vision and AI-based autonomous vehicles designed to detect and predict railway infrastructure damage. 

“Rail tracks play a vital role in supporting public mobility and national logistics distribution, so operational safety must be the top priority. Conventional inspection methods are no longer sufficient to detect damage early and comprehensively,” he explained.

The system integrates high-resolution cameras, night vision, and multiple sensors combined with deep learning algorithms. It can detect and classify various types of rail damage, such as micro-cracks, deformation, and corrosion, in real time, even under low-light conditions. 

Using models such as YOLO (You Only Look Once), Human Pose Estimation (HPE), and QARXNN-CNN (Quasi-linear ARX Neural Network + Convolutional Neural Network), detection accuracy reportedly exceeds 90 percent, enabling faster, data-driven maintenance decisions.

“This detection system is integrated into an Internet of Things (IoT) platform that supports monitoring, data visualization, and automatic notifications for maintenance operators. With this approach, railway infrastructure management shifts from reactive to predictive and preventive, reducing accident risks and improving reliability,” Abu Jami’in added.

Meanwhile, Khairul Anam from the University of Jember highlighted the growing role of autonomous vehicles in healthcare, particularly in hospital environments. 

“Robotics and autonomous systems have advanced rapidly, covering surgical robots, transport and logistics robots, telepresence robots, rehabilitation robots, and smart wheelchairs,” he said.

In hospitals, autonomous vehicles are used to deliver medicines, samples, and medical equipment independently, easing the workload of healthcare staff and minimizing contamination risks. Smart wheelchairs powered by biosignals such as EMG and EEG allow patients with physical limitations to navigate independently using muscle movements, voice commands, or head gestures.

“The autonomous navigation system employs machine learning and deep learning to recognize hospital corridors, detect obstacles, and adapt movement to environmental conditions. Tests have shown promising accuracy under various lighting conditions, opening opportunities for broader application in healthcare facilities,” Khairul concluded.

The integration of AI, robotics, and autonomous vehicles holds significant potential to improve safety, efficiency, and service quality in both transportation and healthcare. 

Looking ahead, cross-disciplinary research and collaboration are expected to accelerate the widespread and sustainable adoption of these technologies, enhancing system performance and ease of operation. ***