Enhanced Cyber-Physical System in Health Care Using LSTM and Bi-LSTM

Complex systems that are developed by integrating communication, computation, and control are known as cyber-physical systems (CPS). Compiling vast amounts of data from various sources worldwide, CPS is a significant player in the healthcare industry. In the healthcare industry, where personal health information is susceptible to data theft and cyberattacks, CPS is essential. This paper presents a comprehensive analysis of cyber-physical systems in healthcare through the use of machine learning models to analyze Enhanced Cyber-Physical Systems in healthcare (ECPS-HC). It shows that the healthcare data are acquired by IOT sensors, stored in the cloud, and analyzed through Machine Learning (ML) and Deep Learning (DL) models. Machine learning models predict the cyber-attacks which helps in decision-making. In order to better understand the design and modeling of CPS in the healthcare industry, this paper will concentrate on how the system architecture integrates LSTM, Bi-LSTM, and the Adam optimizer.