Heart disease is one of the serious health problems faced by many people today. Every year a large number of deaths happen because heart related problems are not detected at the right time. In many cases patients come to know about their condition only when the problem becomes severe. Because of this, regular monitoring of heart health has become very important. With the help of new technologies like Internet of Things (IoT), it is now possible to collect health information from patients and monitor their condition continuously. The main idea of this work is to develop an IoT based system that can help in predicting heart disease by monitoring different health parameters of a person. In this system, sensors are used to measure important body values such as heart rate, body temperature, blood pressure and other related parameters. These sensors are connected with a microcontroller device which collects the data from the patient. The collected information is then sent to an online server or cloud platform through the internet. After storing the data, it can be analy to check whether the health parameters are normal or not. If any unusual change is found in the values, the system can indicate that the person may have a risk of heart related problems. In such cases, alerts can be sent to the doctor or caregiver so that proper medical attention can be given. This kind of system helps in early identification of possible health issues. Another benefit of the system is that it allows remote monitoring. Doctors can check the patient’s health data from different locations without the need for the patient to visit the hospital frequently. This can be helpful for elderly people and patients who need regular health observation. Continuous monitoring also helps in keeping a record of the patient’s health condition over a period of time, which can be useful for medical analysis. The proposed IoT based heart disease prediction system is designed to be simple and affordable so that it can be used easily in healthcare environments. By using connected devices and data monitoring, the system can support early detection of heart problems and help doctors make better decisions. In the long run, such systems can improve patient care and reduce the risk of serious heart complications. One of the major advantages of this system is remote monitoring capability, which allows doctors to access patient data from any location without requiring frequent hospital visits. This feature is especially beneficial for elderly patients, individuals with chronic conditions, and those living in remote areas. Continuous data recording also helps in maintaining a comprehensive health history, which can support better diagnosis and long-term medical analysis. The collected data is transmitted to a cloud-based platform via the internet, where it is securely stored and analyzed using predefined threshold values and predictive techniques. By evaluating the monitored parameters, the system can identify abnormal patterns that may indicate a risk of heart disease. If any irregularities are detected, automated alerts are generated and sent to healthcare professionals or caregivers, enabling timely medical intervention. The proposed IoT-based heart disease prediction system is designed to be cost-effective, user-friendly, and scalable for practical healthcare applications. By combining sensor technology, cloud computing, and intelligent data analysis, the system aims to enhance early detection, improve patient care, and reduce the overall burden of cardiovascular diseases. In the long term, such smart healthcare solutions can contribute significantly to preventive medicine and efficient healthcare management.
Internet of Things (IoT), IoT, Heart Disease Prediction, Artificial Intelligence, Real-Time Monitoring, Heart Disease Prediction, Smart Healthcare System, Remote Patient Monitoring, Wearable Sensors, Real-Time Health Monitoring, Cardiovascular Disease Detection
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