A context-aware data fusion approach for health-IoT

• Published in: International journal of information technology (Singapore. Online) 2018-09, Vol.10 (3), p.241-245
• Main Authors: Baloch, Zartasha, Shaikh, Faisal Karim, Unar, Mukhtiar Ali
• Format: Article
• Language: English
• Subjects: Computer Communication Networks; Computer Science; Computer Systems Organization and Communication Networks; Information Systems and Communication Service; Management of Computing and Information Systems; Original Research; Software Engineering/Programming and Operating Systems
• ISSN: 2511-2104; 2511-2112
• DOI: 10.1007/s41870-018-0116-1

The technological advances in low-cost sensor devices and communication technologies bring rapid increase in development of smart homes and smart environments. The developments in wireless sensor networks (WSN), body area networks (BAN), cloud computing and big data technologies trigger the use of Internet of Things (IoT) in healthcare industry. This poses many challenges such as heterogeneous data fusion, context-awareness, complex query processing, reliability and accuracy etc. Data fusion techniques are used to extract meaningful information from heterogeneous IoT data. It combines individual data from sensor sources to collectively obtain a result, which is more reliable, accurate and complete. Apart from wearable sensors, additional context sensors need to be added to build a context. Health IoT applications has potential benefits of using context-aware data fusion. By using context information, the behavior of the application can be customized according to the specific situation. This paper provides a brief concept of context-aware data fusion and includes data management approach for context-aware systems for healthcare applications. Finally, a context-aware data fusion approach for health IoT is proposed. It includes context acquisition, situation building and reasoning and inference.