Machine Learning and IoT based Disease Predictor and Alert Generator System

Rapidly expanding market of health and increase in the common health issues such as cardiovascular, neurological and pulmonary, sleep, hydration and breath rate disorders motivates researchers to contribute in developing as well as designing systems that accurately observes the body parameter analyses, where the values of monitored parameters and generates alerts if the values show deviation from the standard pre-set values. The monitoring helps in early detection of chronic diseases such as diabetes, heart, respiratory disorders. Devices described in literature faces the challenges such as low reliability, low accuracy and less energy efficient. In this manuscript, authors present a review of existing literature available at national as well as international level. The review focuses on wearable devices such as smart eyewear, wrist band, smart jewelry, sleep track, smart garments and head mounted etc. The challenges identified by the review, motivates the authors to focus on designing a health monitoring frame work. In this manuscript, the authors propose a Machine Learning and IoT based Disease Predictor and Alert Generator System. The ease to use and high reliability proves the usefulness of system in the real time scenario.