In this work, we developed a smart wearable device for gait speed measurement with dual wireless communication on the feet by using an inertia measurement unit (IMU) sensor. To discover step counts and speed information, pitch and yaw angles were calculated successfully from IMU signals using a Kalman filter and a moving average algorithm. Walking step counts were calculated using the sensor; the results demonstrated almost zero errors and averaged more than 90% accuracy in walking and running measurements. The observable speed for two-foot indication and adapted variation can be implemented on the sensor to gauge walking and running speeds for different subjects. Step counts and the swing frequency were tested and compared with results over a treadmill using a commercial chip in the insole of a shoe. Experimental results were validated using fast Fourier transform from the acquired pitch angle history. The pitch and yaw angles of users’ tibias can be used as controllable monitoring tags for personal health information in the future.