An IoT Based Healthcare Solution With ESP32 Using Machine Learning Model

The pandemic in 2020 has brought unprecedented changes in all possible affairs of life and the healthcare sector is no exception to it. The situation stimulated an increment of the overall use of IoT. In healthcare sector IoT can be an impactful add-on to ensure remote healthcare and non-contact treatment of patients. Such facilities can ensure continuous inspection of patients over the time to help in better treatment. Additionally, the real time data clouding can come handy where large number of documentation of data is needed. This paper proposes an IoT healthcare device with embedded temperature, beats per minute and SpO
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and intelligent prediction of one’s health status by machine learning model named LightGBM with a prediction accuracy of 91.12%. Furthermore, data clouding system has also been developed for public and local server to share real time data with other users and doctors. The proposed technology has been designed to assist non-tech users all around the world with a user-friendly approach to get accustomed to smart health care.