Abstract
In this paper, we design and implement an sBike (Sensorized Bike) prototype to support cyclists by recognizing various riding states including going straight, turning right or left, meandering, and stopping. An Android phone, which is equipped with a gyro sensor, an accelerometer, and a GPS receiver, is mounted on the handle of bicycle to collect necessary data for analysis. Hidden Markov model (HMM) is adopted to recognize the riding states from raw sensor data. The experimental results show that the accuracy of recognition is as high as 98%. By knowing the riding states of cyclists, road conditions can be inferred and shared amongst users.
Full Text
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call