IOSR Journal of Engineering (IOSR JEN) www.iosrjen.org ISSN (e): 2250-3021, ISSN (p): 2278-8719 PP 68-73 National Conference on “Recent Innovations in Engineering and Technology” MOMENTUM-19 68 | Page Sharadchandra Pawar College of Engineering, Dumbarwadi, Tal-Junnar, Dist-Pune-410504 Health Care Patient Monitoring using IoT and Machine Learning Dr.Yogesh Kumar Sharma 1 ,Khatal Sunil S 2 1 (Head/Research-Coordinator, Department of Computer Science and Engineering, ShriJ.J.T. University, Rajasthan) 2 (Research Scholar, Computer Department, Shri J.J.T. University, Rajasthan) Abstract: Security and privacy is the most essential thing in Big Data environment, there are many algorithms have been proposed in existing approaches for data privacy as well as security. In many applications like Healthcare are banking applications having available data where third party attacker can easily access the privacy of victims. In Internet of Things (IoT) environment there is the major issue of data security. In this paper we proposed high dimensional Healthcare big data security as well as disease prediction using machine learning approach. Basically the system has categorized into two sections first we implement IoT based environment which generates the data of patient body. This section be used some wearable devices like ECG sensor, BP sensor temperature sensor heart rate sensor etc. Once data has generated from various sensors it will upload on cloud database. In the second phase we monitor the data which is generated by various sensors. Here we have generated Android base graphical user interface with monitors the data 24 by 7. Where machine learning algorithms are has used to predict the disease of patients. The authentication mechanism will achieve role based access control for specific users and proposed machine learning algorithms provides the patient disease probability according to given parameters. The experiment analysis has done based on the partial implementation of system which provide proposed system is more effective than some existing IoT systems.. Keywords: Wearable sensors, healthcare, bigdata, cloud computing, authentication, security. I. Introduction During recent years, rapid evolvement of healthcare services for providing wireless communication media between doctor and patient through wearable technologies which refers in “telemedicine”. The artifact is to provide real-time monitoring of chronic illness such as heart failure, asthma, hypotension, hypertension etc. located far away from the medical facilities like rural area or a person out of health services for a change. In all such circumstances, heart disease becomes leading cause of death due to change in life style applicable for all age groups. Literature narrates approximately 2.8 billion people die because of heart problem due to overweight or obese which ultimately affects cholesterol level, ups and down of blood pressure and more importantly influence of stress hormones on ultimate heart conditions. In much of wearable technologies common parameters of heart functioning like BP, blood glucose level, blood oxygen saturation, ECG etc. were analyzed. In accordance with all these, need of hormonal imbalance due to stress factor i.e. mood of the person (mental health status) and impact of good / bad cholesterol is also deliberated in detail. Basically, the wearable devices accessible within the market embrace smart watches and bracelets, wearable sleep aid devices, etc. because of tremendous advancement in recent years in wearable techniques, these devices square measure loosely accepted within the market by the customers. the info generated from the wearable devices has high rate and thence, it must be hold on and handled carefully at the cloud central information server The wearable sensors live varied physiological information together with electromyography, cardiogram, vital sign, heart rate, vital sign, blood vessel saturation, etc. The advances in wireless communication technology have conquered most of the temporal, geographical likewise as structure barriers to ease a completely roaming means of transferring medical information and documentations to the involved authorities. In this work, a state of affairs within the Cloud of Things central for a sensible medical tending system is taken into account, wherever a collection of wearable device nodes area unit embedded. II. Literature Survey According to de Carvalho Junior et.al. [1] authors had presented the feasibility study and the progress of heart disease classification embedded system. It provides a time diminution on electrocardiogram – ECG signal which can be practiced by decreasing the amount of data samples, without any significant loss. The objective of the urbanized system is the study of heart signals. The ECG signals are subjected onto the system that executes a preliminary filtering, and then utilizes a Gustafson–Kessel fuzzy clustering algorithm in order to exert for signal organization and correlation. The classification denotes usual heart diseases such as angina, myocardial infarction and coronary artery diseases. The system could also be used sudden “on duty” physicians, of any area of expertise, and could afford the first, or initial diagnose of any cardiopathy. If any system detects a