Heart disease is the biggest cause of mortality worldwide. Approximately 80% of deaths happened in underdeveloped and middle-income countries. By 2030, it is projected that 23.6 million people would die from cardiovascular disease if present patterns are allowed to persist. An opportunity to offer an Internet of Things (IoT) solution has become more accessible as the use of smart wearable technology has grown. Furthermore, people who are disabled have a low likelihood of surviving after discharge from the hospital. The present research proposed an IoT-integrated model evaluating temperature, heart rate, and oxygen saturation for predicting the likelihood of the occurrence of heart failure. It has been noted that the proposed model or the hardware system is cost-effective as compared to other expensive sensors that are available in the market. The proposed system used heart rate, oxygen saturation, and temperature as parameters, thus it can make accurate and precise decisions on whether or not an individual has the chance to encounter heart failure and hence can be warned and managed beforehand.