隨著智慧型手機的發展與固態微機電(MEMS)的普及與其技術發展，在手機內嵌微機電系統，或稱慣性感測器讓智慧型手機有著多元化的發展可能性。本論文嘗試使用Android智慧型手機平台實作結合行為辨識的智慧型計步器，讓我們除了系統計步器功能並可以同時計算和取得使用者的行為。在計步器方面使用動態測量的概念，利用雙層平均化濾波的方法達到去除雜訊與同時取得動態平均的效果，令步伐測量的準確度不會依賴手機的指向方位。並將計步器結合行為辨識，利用即時的更新使用者行為讓手機盡量不利用閥值偵測步伐同時提供更多使用者資訊給予參考。實驗結果顯示在我們的即時行為辨識系統之下，擁有的動態回應時間在系統實驗之下均少於5秒。而步伐偵測和行為辨識的精準度與其參考的研究論文比較更為精確。

As the development of the smart phone and MEMS technology comes to more normalization, put inertial sensor into smart is trend and it leads to high range develop possibilities of smart phone. In our thesis, we discussed the implement of pedometer in android platform with activity recognition. User not only get the number of step user takes, but also have information with user’s activity in the same time. In part of pedometer, we use the method of 2-layer moving average filter to remove signal noise and dynamic average. The pedometer’s accuracy should not depend critically on the relationship between the motion axes and the accelerometer’s measurement axes. Meanwhile, we integrate real-time activity recognition method and enhance filter of signal processing, lead to better performance and user information by remove decision of threshold value. In the experiment result, our design of real time activity recognition system depicts that we have dynamic response time which is less than 5 second. As to performance of pedometer and activity recognition, we compare our system with reference paper and obtain better accuracy.

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