With economic development, emission issues have intensified, making environmental protection and green travel subjects of great concern. Cycling has become the preferred choice for the public when going out. However, the low visibility at night poses significant safety hazards for cyclists. This paper has designed and implemented an intelligent bicycle tail light system based on STM32 microcontroller and 3D printing technology, aiming to enhance the road safety of cyclists in nighttime and low-light environments. The system utilizes an MPU6050 six-axis motion sensor to collect the bicycle's motion status in real time. By combining the Kalman filter algorithm to fuse and process the data from the gyroscope and accelerometer, it significantly improves the accuracy and stability of attitude recognition, enabling effective identification of turning and braking intentions.