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It is important to recognize the motion of the user and the surrounding environment with multiple sensors. We developed a guidance system based on mobile device for visually impaired person that helps the user to walk safely to the destination in the previous study. However, a mobile device having multiple sensors spends more power when the sensors are activated simultaneously and continuously. We propose a method for reducing the power consumption of a mobile device by considering the motion context of the user. We analyze and classify the user’s motion accurately by means of a decision tree and HMM (Hidden Markov Model) that exploit the data from a triaxial accelerometer sensor and a tilt sensor. We can reduce battery power consumption by controlling the number of active ultrasonic sensors and the frame rate of the camera used to acquire spatial context around the user. This helps us to extend the operating time of the device and reduce the weight of the device’s built-in battery

Adaptive Power Saving Method for Mobile Walking Guidance Device Using Motion Context