Open AccessA Dynamic Approach to Recognize Activities in WSN
Author(s) -
Muhammad Arshad Awan,
Zheng Guangbin,
ShinDug Kim
Publication year - 2013
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2013/385276
Subject(s) - computer science , activity recognition , usability , ubiquitous computing , wireless sensor network , context awareness , component (thermodynamics) , android (operating system) , human–computer interaction , context (archaeology) , set (abstract data type) , phone , accelerometer , mobile phone , key (lock) , context management , embedded system , machine learning , operating system , paleontology , linguistics , philosophy , physics , biology , thermodynamics , programming language
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.
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