IoT-Based Health Big-Data Process Technologies: A Survey

• Hyun Yoo,
• Roy C. Park,
• Kyungyong Chung,

Vol. 15, No. 3, March 31, 2021
10.3837/tiis.2021.03.009, Download Paper (Free):

• Data Mining
• XAI
• Cloud
• IoT
• Healthcare
• WBAN
• Big data
• Deep Learning

Abstract

Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things–based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.

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