Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Big IoT Healthcare Data Analytics Framework Based on Fog and Cloud Computing

  • Alshammari, Hamoud (Dept. of Computer Science, College of Science and Arts, Jouf University) ;
  • El-Ghany, Sameh Abd (Dept. of Information Systems, College of Computer and Information Sciences, Jouf University) ;
  • Shehab, Abdulaziz (Dept. of Computer Science, College of Science and Arts, Jouf University)
  • Received : 2020.02.11
  • Accepted : 2020.08.23
  • Published : 2020.12.31
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Abstract

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.

Keywords

Acknowledgement

We are indebted to the Deanship of Scientific Research at Jouf University for funding this work through General Research Project (No. 40/201).

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