Machine learning approach for sensors validation and clustering

Wireless sensor network (WSN) is very important these days. It is used frequently in many applications in the area such as health care, security, home and military. As the sensor nodes in the domain may change over the time due to number of factors such as environment condition, lifetime of the battery (low battery power) and coverage (area of interest), then a sensor network needs periodically to check the validation of sensor in the domain. So, as needed of the sensors validations in the domain have been shown in many WSN schemes. In this paper, the validation sensors in the domain using spectral clustering technique have been proposed that is detecting a bad sensor and deleting it from the domain. Sensors have been indexed by their location using simple model of spectral clustering. Results obtained from simulation indicate that our approach is enhanced network performance in terms of detecting the bad sensor location and replace it that is improved our wireless sensor network.