Human activities recognition in smart living environment

Human activity recognition has been changing the way people live through smart homes. Machine learning algorithms are used to accurately detect human activities at home. The usage of cameras can be considered invasive to some home owners, therefore alternate kind of sensors have to be used. Mobile phones provide a good range of sensors to test and also to detect the various types of activities. This paper examines different data sets for comparison, how accelerometer, gyroscope as well as pressure sensors cam be used in detecting the various activities. MATLAB’s classificationLearner application will be used in this experiment to aid in quick and accurate testing, as well as visualising of dataBachelor of Engineerin