IOT Big Data Analytics in Healthcare: Benefits and Challenges

Abstract

Medical data is being generated from a wide variety of sources today, including smart phones, wearable sensors, patient records, clinical reports, researchers, healthcare professionals, and organizations. Healthcare data has the potential to support rapid decision making processes in detection of critical diseases and pandemics. The widespread acceptance of the Internet of Things (IOT) has brought challenges for analytical systems, because heterogeneous, complex and un-structured data has to be processed and stored in real time. The incorporation of big data analytics (BDA) of the Internet of Things is vital to reducing healthcare costs and identifying risks. The design, however, has a staggering complexity that requires the use of sophisticated technologies and techniques. Using Deep Learning techniques, Machines can be trained with Artificial Intelligence to support the medical industry in various ways. This paper describes how the IOT Analytics are beneficial in the healthcare domain and discusses the challenges in it.