Jakarta, INTI - To address microsleep issue that causes motorcycle accidents, students from Institut Teknologi Bandung (ITB) designed an Internet of Things (IoT)-based sensor helmet. The innovation was showcased at the Smart Safety Competition (SASECOM) 2026.
The iConic team, consisting of Mahesya Friemay Romadhoni, Muhammad Yasser Saputro, Rizky Miftah Alfiah from the Industrial Engineering class of 2023, developed a smart helmet innovation called the SADAR Helmet. This technology can provide preventative warnings through vibrations, sounds, and digital notifications to prevent accidents.
The SADAR Helmet integrates Photoplethysmography (PPG) sensor, accelerometer, and gyroscope to monitor the rider's physiological condition and head movements.
The helmet not only serves as protection during an accident but is also capable of detecting pre-microsleep conditions before an accident.
The system utilizes a combination of multisensors for more accurate detection results, can be retrofitted to SNI-standardized helmets without changing the helmet's structure, and has a relatively affordable implementation cost compared to camera- or EEG-based systems.
Technologies Used in SADAR Helmet
In its development, the team used IoT technology for data monitoring and communication, PPG sensors to read heart rate and Heart Rate Variability (HRV), and accelerometers and gyroscopes to detect head movement patterns.
The system utilizes machine learning and sensor fusion to classify driver drowsiness. For safety assessment, the team employed the Heinrich's Accident Triangle, Domino Theory, Swiss Cheese Model, and Hierarchy of Controls approaches based on NIOSH and ISO 45001.
"The process took a long time because we really brainstormed for days to come up with the idea for the SADAR Helmet. Coincidentally, we were also taking a Product and Business Development course, and K3 was one of the subjects studied in Industrial Engineering," said Rizky.
This innovation aims to be further developed through the integration of a mobile app, GPS tracking, cloud monitoring, and AI-based analysis to improve the accuracy of drowsiness detection. The team also hopes to collaborate with the helmet industry, the automotive sector, and the government to ensure this innovation can be produced and widely used.
Conclusion
The ITB Industrial Engineering student team, iConic Team, developed the SADAR Helmet, an IoT-based smart helmet to detect microsleep and prevent accidents. This technology combines Photoplethysmography (PPG) sensors, accelerometers, and gyroscopes to monitor the driver's heart rate, heart rate variability, and head movements. The system then utilizes machine learning and sensor fusion to identify drowsiness and provide warnings through vibration, sound, and digital notifications. Another advantage is that the device can be installed on SNI-standard helmets without changing the helmet structure.
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