International Research Journal of Education and Technology

Coronary heart disease is the leading cause of death worldwide. For dealing with those in need, the human services field contains a wealth of information.Certain methods are used to collect information. One of the most common methods is handling or processing. This strategy forecasts the potential outcomes of cardiovascular disease. The outcome of this strategy is to predict the previous cardiovascular malady. The task manages IOT using a sensor (a pulse sensor to monitor pulses) and Arduino, and the results can be viewed in a sequential screen. IFTTT is used to analyze sensor readings in Google Sheets, which are then converted into csv files that look like data. The datasets used are classified according to therapeutic parameters, which are also used for data preparation and testing. This strategy evaluate.These parameters are set using the information preparation order method. With AI calculations and classification work.The dataset is first dissected, watched, and screened, after which the obtained data is handled in Python programming using Machine Learning Algorithms, specifically Decision Tree Algorithm and Random Backwoods Classifier Algorithm.

Keywords—Health Care System, IOT, Machine Learning Techniques, SVM Classifier