Adaptive Context-Aware Design Using Context State Information for the Internet of Things Paradigm


  • Derrick Ntalasha School of Information and Communications Technology, Copperbelt University, Jambo Drive, Riverside, Kitwe, Zambia
  • Renfa Li College of Information Science and Engineering, Hunan University, Lushan Road Changsha, 410082, China
  • Yongheng Wang College of Information Science and Engineering, Hunan University, Lushan Road Changsha, 410082, China



Context adaptation, context event alignment, context state information, finite state machine, semantic localization


In the Internet of Things (IoT) paradigm, context state information plays a critical role in advancing the development of adaptive pervasive applications. Pervasive services and context-aware computing are emerging as the next computing paradigms in which infrastructure and services are seamlessly available anywhere, anytime, and in any format. The IoT paradigm raises new opportunities and demands on the underlying systems, in particular, the need to have systems that are adaptive and context-aware using context state information. In this paper, we introduce a new adaptive context state design technique to model context-aware applications that are sensitive to context state information changes. Each context change event is captured, interpreted and reacted to so that applications and users use only the functionality and adaptability needs that are solutions to their needs. The solution is modeled using Finite State Machine (FSM) and semantic localization so that context state information within the IoT paradigm is aligned to events. The semantic localization process precisely estimates the proximity location of the user along with the quality of context (QoC) attributes using the Bluetooth cell-based approach. This semantic information is useful in determining and inferring the user activities in a location. The QoC attributes are used to determine the confidence of the user location and range of the Bluetooth beacons within the IoT domain. This will, in turn, be used to determine whether the user is in the location or not. The alignment technique in our model represents the proper and new solution concerning functionality and adaptability needs expressed by other user applications in the IoT environment. The experimental scenario results indicate that a user can continue to enjoy their daily activities while the IoT application adapts continuously to their changing needs and notifying service providers of the changes according to the events of the user.


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Author Biographies

Derrick Ntalasha, School of Information and Communications Technology, Copperbelt University, Jambo Drive, Riverside, Kitwe, Zambia

Derrick Ntalasha was born in Zambia, in 1978. He received the BSc. Computer Science degree from the Copperbelt University (CBU) in Zambia, in 2002 and an advanced MSc. degree from the University of Manchester United Kingdom, in 2005, Information Systems Engineering. He has a Ph.D. degree in Computer Science and Technology from the College of Information Science and Engineering, Hunan University, China. His research interests are Context awareness computing and Internet of Things (IoT). He is currently the head of computer science Department in the School of Information and Communications Technology at the Copperbelt University.

Renfa Li, College of Information Science and Engineering, Hunan University, Lushan Road Changsha, 410082, China

Renfa Li is currently the President and Ph.D. supervisor of computer science within the School of Computer and Communication, Hunan University, with specialty in the fields of Computer architecture and computer application technology (CAT).

He has been a chief investigator on research grants totaling over RMB 1,000,000 from sources including Natural Science Foundation of China (NSFC) and others at state or provincial level. He has published over 60 scholarly papers in journals, book chapters and international conferences and acted as editor of a dozen books in recent years.

Professor Li is a councilor of China Computer Federation, a senior member of the Institute of Electronic and Electrical Engineers, a senior member of the Association for Computing Machinery.

Yongheng Wang, College of Information Science and Engineering, Hunan University, Lushan Road Changsha, 410082, China

Yongheng Wang was born in Hebei, China, in 1973. He received the Ph.D. degree in computer science from the National University of Defense Technology, Changsha, China, in 2006. Since December 2008, he has been working as a teacher at the College of Information Science and Engineering, Hunan University. His research interests include data mining, event processing and big data.


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