Machine Learning Algorithms for Disease Prediction Using Iot Environment 
Samir S. Yadav1, Shivajirao M. Jadhav2
1Samir S. Yadav*, Research Scholar and Assistant Professor, Information Technology Department, Dr.Babasaheb Ambedkar Technological University, Lonere, India.
2Dr. Shivajirao M. Jadhav, Professor and Head, Information Technology Department, Dr. Babasaheb Ambedkar Technological University, Lonere, India.
Manuscript received on July 30, 2019. | Revised Manuscript received on August 25, 2019. | Manuscript published on August 30, 2019. | PP: 4303-4307 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8914088619/2019©BEIESP | DOI: 10.35940/ijeat.F8914.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the most advanced healthcare application environment, the use of IoT technologies brings convenience to medical professionals and patients, since they have applied to health areas. In IoT, Body sensor network (BSN) technology plays a vital role in the healthcare system where lightweight wireless and low-powered sensor nodes used for monitoring the patients. In this paper, we propose a healthcare system using IoT and BSN technology. This system includes various sensors like pulse rate sensor, temperature sensor, and blood pressure sensor. These sensors sense the parameters and send the data to the controller. According to the conditions, the buzzer will on as temperature exceeds the given range. It carries the sensed data to the LCD to display on it. At the same time, data send to doctors using the internet, so that they can give quick and proper solution in real-time. Many patients suffer because of not getting the timely and appropriate solution and help for their problem. Proposed system hence offers the real-time solution and help in case of emergency. This system is convenient; therefore, a person can carry it with them. Thus continuous health checking is possible. The system also predicts the disease for a particular patient base on current reading using various supervised learning algorithms.
Keywords: Machine Learning, Internet of Things (IoT), Body Sensor Network (BSN), Fuzzy Random Forest (FRF)