Authors: Bharat Prajapati, Satyen Parikh, Jignesh Patel Abstract:Researchers have been endlessly contributing to discover Cardiovas-cular diseases (CVDs) in an early stage using various intelligent practices when a report published by the WHO - World Health Organization shows internation-ally CVDs are the primary reason for human deaths in 2017. They have been trying to control and prevent through various Global Hearts Initiatives. WHO also mentioned major risk factors for cardiovascular disease. These factors might be the use of Tobacco, physical activity, consumption of high sault in daily food, consumption of foods with TRANS-FATTY acids and high blood pressure [1]. As per number published by the WHO, around 17.9 million (179 lakh) deaths were responsible due to cardiovascular in 2016. Heart attacks and strokes were the topmost reasons. Internet of Things (IoT) empowers people to get an advanced level of automating by evolving a system with the help of sen-sors, interconnected devices, and the internet. In the health care segment, pa-tient monitoring is a very critical and most vital activity since a small delay in decision-related to patients’ treatment may cause permanent disability or maybe death. Most ICU devices are furnished with various sensors to measure health parameters but to monitor it all the time is still a challenging job. In our re-search, we have proposed an IOT based intelligent model, which captures the various body parameters using the bedside monitor and discover the early stage CVDs disease using supervised machine learning classification algorithms. To improve the accuracy of the model, we have also used multiple algorithms to achieve better accuracy.
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