Role of data analytics in bio cyber physical systems

Abstract

Data science has proved its versatility in all dynamics of the field known to mankind, making decision making faster, and accurate over the past two decades. Coupled with IoT devices and their setups, these have been forerunners in terms of data generation and accurate prognosis. According to advisory firm International Data Corporation (IDC), the number of IoT devices is forecasted to reach 41.6 Billion by 2025, and the data generated from these devices is expected to be 79.4 Zettabytes. One broad sector which has emerged as a gold mine for data generation is the Bio Cyber Physical Systems. Bio Cyber Physical Systems are based on the incorporation of computational elements with biological processes of the human body. The following chapter aims to discuss a new design, implementation of a system based on Bio-CPS, focused primarily on health wearable technologies equipped with state-of-the-art sensors, couple their data with machine learning algorithms to detect real-time health complications primarily in a diabetic person and use of long short-term memory (LSTM) for prediction of such health complications.