The widespread use of smartphones, tablets, and other electronic gadgets has made them essential to daily life in the current era of communication and technology. The Internet of Things (IoT) is a rapidly developing paradigm for the linked world that links gadgets, sensors, appliances, cars, and other things. This research presents an intelligent Internet of Things system that uses Electrodermal Activity (EDA) sensors to forecast paroxysms proactively. The technology uses machine learning methods to combine EDA sensor data with real-time prediction of cardiac events and other health problems. The suggested system presents a promising method to remote health monitoring and early intervention through data analysis and continuous monitoring, with the potential to improve patient outcomes and save lives.