In recent times, health problems like cardiac failure, lung failures and heart related diseases are arising day by day at a very high rate. To address these problems, a sustained health monitoring becomes imperative. By regular health monitoring, diseases can be diagnosed and treated early. A new concept which is emerging is by monitoring the health of a patient wirelessly. In this paper, we report the use of a body temperature sensor and a heartbeat sensor for an IoT-based health monitoring system. The set up involved relaying of data from the sensors to an Arduino which was then sent to the cloud via an Ethernet module. The collected data were further processed by applying various algorithms and classification was done. We present the results obtained from the processing of the data using various algorithms-Naive Bayes, Random Forest Tree and SVM-and their comparison based on accuracy, precision and classification time. © BEIESP.