Wearable and self-powered triboelectric sensors based on NaCl/PVA hydrogel for driver multidimensional information monitoring

Abstract

Dangerous behaviors during driving such as fatigue or making phone calls may seem common in daily life. However, these behaviors are the actual "culprit" of many traffic accidents and pose a serious threat to traffic safety. Therefore, it is necessary to effectively detect dangerous driving behaviors by scientific and technological means. The present detection methods still face many bottlenecks, including individual differences, complex lighting changes, battery power supply, poor wearability, et al. Here, we designed a green and stretchable triboelectric sensor (TES) to monitor dangerous driving behaviors. The performance of the sensor was improved by about 9.99 and 3.58 times through doping sodium chloride solution in PVA hydrogel and introducing a curved contact surface between the electrode and friction layer, respectively. The proposed sensor has a high sensitivity of 1.95 V/kPa in the linear range of 0–11.28 kPa. By employing different machine learning models, we developed an intelligent neck ring based on the proposed sensor array to recognize different neck movements, which has achieved the highest accuracy of 96.10%. Finally, the intelligent neck ring was used to construct a sensing system for driver status monitoring. By collecting detailed driver information, the system can detect dangerous driving behaviors, monitor drivers’ health conditions, and provide appropriate reminders to improve driving safety and prevent the spread of viruses.