  Wireless Sensor networks are used to monitor remote areas. Wireless sensor
network can be applied to monitor a facility by considering each camera as
sensor nodes. Cameras are used as nodes in a wireless sensor network with a
central server or a gateway node for all the monitoring and analysis of the
information retrieved from the nodes. Identification and authentication of
users in any organization is quite difficult due to high movement. Face
recognition can be used detect faces and identify them continuously in a video
feed which can be deployed to continuously monitor an area. Feeding from camera
to base station uses Multi-task Cascaded Convolutional Neural Networks (MCTNN)
and FaceNet algorithms for face recognition. Further information about the
person is sent to all the end-user nodes present in the wireless network. This
approach has been implemented and evaluated on a prototype wired camera network
called FaceNet. A method for tracking people in 2D world coordinates and
acquiring canonical frontal face images that fits the sensor network paradigm.
The approach evaluates and demonstrates the tasking algorithm in action on data
acquired from the FaceNet camera network. In this paper, face recognition
algorithm FaceNet is used to implement security monitoring network
