International Journal of Engineering and Technology

Wireless sensor networks monitor the environment with various types of sensors. Environment in its broader terms can be the geographic environment or it can be our human body. One such type of network is Wearable and Implantable Body Sensor Network (WIBSN). This paper focuses on processing of data generated from WIBSN. WIBSN includes a network of sensors that generate different type of values. This paper treats each sensor as a dimension in the whole dataset. In this case, data may have both continuous and discrete values. Hence; proposed work can be applicable for both of those data values. By identifying nature of the sensor data model, underlying similarity or dissimilarity measure is selected. A novel Crisp clustering technique is used to simulate the proposed work.