作者: Tahani Daghistani , Riyad Alshammari
DOI: 10.14569/IJACSA.2016.070520
关键词:
摘要: In line with the increasing use of sensors and health application, there are huge efforts on processing collected data to extract valuable information such as accelerometer data. This study will propose activity recognition model aim detect activities by employing ensemble classifiers techniques using Wireless Sensor Data Mining (WISDM). The recognize six namely walking, jogging, upstairs, downstairs, sitting, standing. Many experiments conducted determine best classifier combination for recognition. An improvement is observed in performance when combined than used individually. built AdaBoost decision tree algorithm C4.5. effectively enhances an accuracy level 94.04 %.