ZigBee Technology is a wireless communication technology. Wireless Communication is not a new technology as we already have short range communication standards, like Wi-Fi and Bluetooth. But ZigBee is specially built for control and Sensor networks. Other wireless technologies are not quite suitable for this specific application. ZigBee is a wireless technology standard that defines a set of communication protocols for short range communications. This paper gives an overview of the ZigBee Technology and it covers ZigBee working, applications and some of general characteristics of ZigBee standard.

Face recognition system is one of the biometric information process. Its applicability is easier and working range is wider than other biometric systems like signature, fingerprint, iris, etc. This paper proposes, a face recognition based authentication scheme for automated teller machine banking systems. The designed detection method extract face features from input image. The output image of the face detection algorithm has to be similar with the input image recognized for successful authentication. The proposed PIC18F458 Microcontroller based face recognition biometric scheme is successfully fused with the automated teller machine banking system for personal authorization with increased social security.

Face recognition system is one of the biometric information process. Its applicability is easier and working range is wider than other biometric systems like signature, fingerprint, iris, etc. This paper proposes, a face recognition based authentication scheme for automated teller machine banking systems. The designed detection method extract face features from input image. The output image of the face detection algorithm has to be similar with the input image recognized for successful authentication. The proposed PIC18F458 Microcontroller based face recognition biometric scheme is successfully fused with the automated teller machine banking system for personal authorization with increased social security.

The diagnosis system presents to classify the Electroencephalogram (EEG) brain signal of patient to distinguish between normal and abnormal which are tumor and epilepsy with better classification accuracy. To design automated classification of EEG signals for the detection of normal and abnormal activities using Wavelet transform and Artificial Neural Network (ANN) Classifier is considered. Here, the system uses the back propagation with feed forward for classification which follows the ANN classification with data set training. For training, the statistical principal features will be extracted with facilitate of data base samples. The test sample is going to be classified using ANN classifier parameters and its features. The system gives better performance accuracy for different test samples

The diagnosis system presents to classify the Electroencephalogram (EEG) brain signal of patient to distinguish between normal and abnormal which are tumor and epilepsy with better classification accuracy. To design automated classification of EEG signals for the detection of normal and abnormal activities using Wavelet transform and Artificial Neural Network (ANN) Classifier is considered. Here, the system uses the back propagation with feed forward for classification which follows the ANN classification with data set training. For training, the statistical principal features will be extracted with facilitate of data base samples. The test sample is going to be classified using ANN classifier parameters and its features. The system gives better performance accuracy for different test samples