Energy Efficient Human Activity Recognition using Hybrid Mobile Application Development Approach

Ms. Puja B. Patil, Mrs. D. B. Gothawal

Abstract


Activity recognition is formulated as a classification problem. Human activity recognition(HAR) receives more attentions in recent years, due to many of it’s applications, such as health care, video surveillance and context-aware computing.Human activity are recognized from accelerometer data. Now a days, smartphone are used intensively so the key benefits of using the smartphone accelerometer for human mobility analysis,with or without location determination based upon GPS, WiFi or GSM is that accelerometer is energy-efficient, provides real-time contextual information and has high availability. Using measurements from an accelerometer for human mobility analysis presents its own challenges as all carry smartphones differently and the measurements are body placement dependent.Therefore a novel algorithm is proposed that neutralizes the effect of different smartphone on-body placements and orientations to allow human movements to be more accurately and energy-efficiently identified. We proposed android application AT(Activity Tracker) to collect dataset which runs on android and iOS, record accelerometer data with 40hz frequency like 40 samples per seconds.

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