The iConic team, consisting of Mahesya Friemay Romadhoni, Muhammad Yasser Saputro, and Rizky Miftah Alfiah from Industrial Engineering class of 2023, won 2nd place nationally among 80 finalists in the Scientific Paper category. They presented an innovative IoT-based smart helmet capable of detecting microsleep in motorcycle riders in real-time and issuing preventive alerts through vibration, sound, and digital notifications to prevent accidents.

The competition consisted of two selection stages, beginning with the scientific paper submission and concluding with an online pitch deck presentation.

The SADAR Helmet was developed to address the high incidence of traffic accidents caused by microsleep and rider fatigue in Indonesia. The team noted that many fatal accidents occur when riders lose consciousness for several seconds without realizing it. At the same time, most existing vehicle safety systems are reactive, operating only after an accident occurs rather than preventing it from the outset.

This innovation integrates Photoplethysmography (PPG) sensors, accelerometers, and gyroscopes to monitor riders’ physiological conditions and head movements. “We chose this topic because microsleep is a real and highly relevant issue in Indonesia, especially for motorcycle users, who dominate national accident statistics. Advances in IoT and smart mobility also create significant opportunities for a more preventive, affordable, and easily implementable safety system,” said Mahesya.

The SADAR Helmet’s strength lies in its preventive, real-time approach. The helmet not only protects riders during accidents but also detects pre-microsleep conditions before accidents occur. The system uses multi-sensor combinations for more accurate detection, can be retrofitted onto standard SNI helmets without altering their structure, and has a relatively lower implementation cost compared to camera- or EEG-based systems.

In its development, the team employed IoT technology for monitoring and data communication, PPG sensors for heart rate and Heart Rate Variability (HRV) measurement, and accelerometers and gyroscopes to detect head movement patterns. The system uses machine learning and sensor fusion to classify riders’ drowsiness conditions. For the safety assessment, the team applied Heinrich’s Accident Triangle, Domino Theory, Swiss Cheese Model, and the Hierarchy of Controls based on NIOSH and ISO 45001.

“The process took a lot of time because we truly brainstormed for days to develop the SADAR Helmet concept. Coincidentally, we were also taking the Product and Business Development course, while K3 (occupational safety and health) is one of the study objects in Industrial Engineering,” explained Rizky.

The biggest challenge during the competition was the short preparation time. The team had to write the paper, create prototype designs using SolidWorks and AutoCAD, and validate safety measures based on relevant scientific journals. Amid academic demands, they scheduled group work after classes.

Team iConic hopes the SADAR Helmet will become a vehicle safety innovation capable of reducing accidents caused by microsleep in Indonesia. They aim to further develop the system through mobile app integration, GPS tracking, cloud monitoring, and AI-based analysis to improve drowsiness detection accuracy. The team also hopes to collaborate with the helmet industry, automotive sector, and government to enable widespread production and use.

“We learned that the success of an innovation does not only come from a good idea, but also from strong research, teamwork, effective communication, and the ability to understand real societal problems,” said Yasser.

Reporter: Rasya Ihza Ramadhan (Physics Engineering, 2023)