Principal Component Analysis in Body Sensor Networks for Secure Data Transmission

With the adoption of Internet of Things, the reconciliation of clinical gadgets and medical treatments’ gear has come to pass superior treatments and diagnosis. This would additionally help in remote health monitoring through wearable gadgets and to counsel specialists through associated applications directly. This paper deals with the data collected from various sensors that are connected to a body sensor network and which forward data to destination nodes. With a greater number of sensor data, it is difficult to analyze whether sensor readings are correct or not? Sometimes, this becomes tedious if number of sensors is more. In addition, the data may be corrupt increasing the vulnerability of applications dependent on such data. Hence, the reduction in the dimension of sensors is required for a robust and accurate decision making. This paper presents a principal component analysis for the dimension reduction in sensor networks with the aim to analyze the sensor network data to facilitate secure data transmission.