The essence of context awareness has changed the revolution of ubiquitous computing, and the wireless sensor network technologies paved the way towards many applications. Activity recognition is a key component in identifying the context of a user for providing services based on the application. In this study, we propose a context management model that is based on activity recognition. The model is composed of four components: a set of sensors, a set of activities, a backend server with machine learning algorithms, and a GUI application for the interaction with the user. A prototype is developed to show the usability of the proposed model. As a pilot testing, only accelerometer data of an Android phone is used to identify the activities of daily living (ADLs): sitting, standing, walking, and jogging. A good accuracy of results that is about 96% on average is achieved in all activities.
|Journal||International Journal of Distributed Sensor Networks|
|Publication status||Published - 2013 May 27|
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications