| abstract |
The invention discloses a non-interference monitoring method used for identification of extremely small risks in intelligent network-connected control, and belongs to the field of driving behavior monitoring. The realization method of the invention is to prepare a stretchable polyacrylamide PAAM-licl-based triboelectric nanogenerator PL-TENG and a triboelectric nanogenerator AK-TENG with an aluminum AI-Kapton friction layer structure. Build an intelligent networked simulated driving scene to obtain natural driving data. The PL‑TENG is placed on the driver's eyes, mouth, neck, etc., and converts the extremely small movements of the driver's face and head into electrical signals, which are obtained from the collected electrical signals to characterize fatigue and distraction The characteristic indicators of the AK‑TENG are arranged on the steering wheel and pedals to convert the driver’s tiny movements when completing steering, acceleration and braking operations into electrical signals, and use the voltage data to complete the establishment of a risky driving operation identification model. Combining two kinds of triboelectric nanogenerators realizes the uninterrupted real-time monitoring of the driver's driving state and driving behavior. |