A Wireless Integrated System with Hybrid Embedded Sensing for the Continuous Monitoring of Bird Flight

The intricate flight patterns exhibited by birds have sparked considerable interest in many fields. However, traditional external visual observation has significant limitations, including susceptibility to line-of-sight occlusion, uneven lighting effects, and lack of continuous detection. In this paper, we design a hybrid embedded system that can perform bird flight postures recognition by integrating inertial measurement unit (IMU) with flexible strain sensor. The proposed system leverages a strain sensor based on laser-induced graphene (LIG), strategically positioned on the bird's wing joints, in conjunction with a high-precision IMU deployed on the bird's torso. Through a learning architecture, we achieve an impressive accuracy of 99.48% in identifying eight commonly observed bird flight postures. The integration of the proposed system offers exciting possibilities and serves as a powerful tool for advancing our understanding of the mechanisms underlying creature flight.