Paradigm of IoT big data analytics in the healthcare industry: A review of scientific literature and mapping of research trends

Abstract Health informatics and telematics have been drastically influenced by big data of IoT devices. In this paper, we conducted a review of scientific literature and mapping of research trends on IoT Big Data Analytics paradigm (IoTBDA) in healthcare industry. The goal is to identify how the IoT BDA paradigm has impacted the design, development, and application of IoT based innovations in healthcare services. We conducted a qualitative and quantitative review of 46 papers on IoTBDA, and a quantitative review of 84 papers on fog computing in the healthcare industry. This study shows that IoT BDA has impacted the acquisition, storage, retrieval, and use of information in healthcare industry. Consequently, three derivers of IoT BDA convergence are identified. The first driver is computing; which is emerged as a response to reduce data congestion and inefficiencies of emergency systems. As the co-word analysis shows, issues such as security, privacy and data transfer are dominant scientific topics within the domain of fog computing. The second driver of convergence is the storage of IoT big data. This has led the researchers to classify IoT data to critical and non-critical data; while the critical data is sent to fog systems; non-critical data is sent to centralized cloud systems. The third driver of convergence is data abstraction. The study shows that IoT BDA has sparked the emergence of novel health applications and systems. This paper extends the literature on health informatics and telematics and our understanding of everyday practice of these systems in healthcare contexts. Since IoT BDA and fog computing in healthcare are new fields, findings of this study can act as a basis for future studies to determine novel research opportunities on IoT BDA.

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