학술논문

Web Based Disease Prediction and Forecasting with KNN and RNN using Internet of Medical Things
Document Type
Conference
Source
2022 International Conference on Computer, Power and Communications (ICCPC) Computer, Power and Communications (ICCPC), 2022 International Conference on. :192-198 Dec, 2022
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Recurrent neural networks
Oxygen
Sociology
Predictive models
Prediction algorithms
Skin
Forecasting
Recurrent neural network (RNN)
K-Nearest Neighbor (KNN)
IoT Simulator
Arduino Uno board (ESP8266)
Language
Abstract
Maintaining a healthy lifestyle has been a difficult task for all the busy workers and innovators. In this fast growing era, detection of disease at the right time can save millions of life. But proper monitoring after detection is difficult. Emerging infectious diseases pose a growing threat to the human population. To Overcome this, a web based application which predicts the disease and forecast the health condition of the user and help them to maintain a healthy lifestyle is developed. The application is divided into two parts. One is ML based disease prediction using KNN algorithm. In this module, most common diseases are predicted for the body parts like Skin, Eye, Ear, Nail and Teeth using the symptoms entered by the user. They can also find the risk level of the disease and treatment for that specified disease. Other one is Forecasting and report generation using RNN algorithm. This module contains classification and forecasting of user's health using the data fetched from the lot simulation. The parameters used here are Heart Beat, Temperature, Blood Pressure and Oxygen Level. The reports with graphical representation is implemented for the better understanding of the user. The web application also includes the doctor's suggestion who are specialists to that particular disease. As an added feature, health and food tips with precautions to be taken to control the disease are given to the user.