Machine Learning Approach for Cloud Data Analytics in IoT

11Advancement of Machine Learning and Cloud Computing in the Field of Smart Health Care

Aradhana Behura^*, Shibani Sahu^† and Manas Ranjan Kabat^‡

Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

Abstract

An important application of WSN (Wireless Sensor Network) is WBAN (Wireless Body Area Network) which is utilized to monitor the health by taking the help of cloud computing and clustering, which is a part of machine learning. The sensors can measure certain parameters of human body, either externally or internally. Sensor Nodes (SNs) normally have very limited resources due to its small size. Therefore, an essential design requirement of WBAN schemes is the minimum consumption of energy. BioSensor Nodes (BSNs) or simply called as SNs are the main backbone of WBANs. It is used to sense health-related data such as rate of heart beat, blood pressure, blood glucose level, electrocardiogram (ECG), and electromyography of human body and pass these readings to real-time health monitoring systems. Examples can include measuring the heartbeat and body temperature or recording a prolonged ECG. Several other sensors are placed in clothes, directly on the body or under the skin of a person, and measure the temperature, blood pressure, heart rate, ECG, EEG, respiration rate, etc. Increasing health monitoring needs and self-awareness of the population motivates the need of developing a low energy and maximum lifetime network-based routing protocol. Medical application ...