Open AccessAnalysis of Supervised Machine Learning Techniques for Diagnosis of Disease of Infant Baby
Author(s) -
Avali Banerjee,
Surjit Paul,
Santanu Saha,
Surjit Paul
Publication year - 2021
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst0706002
Subject(s) - microcontroller , computer science , cloud computing , node (physics) , controller (irrigation) , real time computing , artificial intelligence , embedded system , engineering , operating system , agronomy , structural engineering , biology
A system for monitoring an infant's health is developed and described in this paper. In this system, smokedetector, sound sensor, temperature and humidity sensor, are interfaced with the controller NodeMCU-ESP8266. In the system, ThingSpeak Cloud is used for the data processing. ThingSpeak Cloud isconnected to the Wi-Fi based microcontroller. The behavior and the problems that are being detected can beeasily notified to the parents apart from the doctors and nurses, So, that even the nurses or the doctorsmisses out by chance, the parents can handle the scenario. The collected data can be taken out as in the formof the csv format. This data can be easily put into the Machine Learning Model in order to predict the variousproblems that a baby might be suffering from. These predictions have been done solely upon the datacollected from the individual baby. Furthermore, separate system-based report would be facilitated by themodel itself