IMHS: An IoT-Based Machine Learning Healthcare System

Innovative solutions have been made possible by the quick development of technology in many fields, including healthcare. Healthcare is being revolutionized by the fusion of Internet of Things (IoT) and (ML) Machine Learning, which has emerged as a disruptive strategy. With the goal of enhancing patient care, improving diagnostics and streamlining healthcare procedures, this article investigates the concept, implementation and impact of an IoT-enabled healthcare system based on machine learning. The healthcare industry will function more effectively, reduce healthcare expenditures, increase patient safety and make healthcare services more accessible.In addition to increasing accessibility to healthcare services, lowering healthcare costs, and improving patient safety, the healthcare industry will run more smoothly. The accuracy, precision, F1-score, and recall of four distinct machine learning algorithms: first one is Decision Tree (DT), second is K-Nearest Neighbor (K-NN), third is Naïve Bayes (NB) and last Support Vector Machine (SVM) are evaluated in this method.