Data Mining Technique based Ambient Assisted Living for Elderly People

Ambient assisted living plays a vital role in assisting the elderly people. There will be a significant amount of rise in the population of the elderly people in the future. Elderly people must need an assistance to enrich their lifestyle. To provide such an opportunity, human activity recognition (HAR) will be of great use. Monitoring day to day activities are essential to assist independent elders. In this paper, we have collected a dataset of 5 daily activities using accelerometer and gyroscope from elders and used data mining techniques such as KNN and Random forest for classification. We have achieved an accuracy of 88 % using KNN and 89% using random forest. The results obtained are favorable in recognizing the activities to the greater extent.