In the field of pattern recognition multiple classifier systems based on the combination of outputs from different classifiers have been proposed as a method of high performance classification systems. The objective of this work is to develop a fuzzy Gaussian classifier for combining multiple learners, we use a fuzzy Gaussian model to combine the outputs obtained from K-nearest neighbor classifier (KNN), Fuzzy K-nearest neighbor classifier and Multi-layer Perceptron (MLP) and then compare the results with Fuzzy Integral, Decision Templates, Weighted Majority, Majority Naïve Bayes, Maximum

The internet of things (IoT) has provided a promising opportunity to build powerful systems and applications. Security is the main concern in IoT applications due to the privacy of exchanged data using limited resources of IoT devices (sensors/actuators). In this paper, we present a classification of IoT modes of operation based on the distribution of IoT devices, connectivity to the internet, and the typical field of application. It has been found that the majority of IoT services can be classified into one of four IoT modes: Gateway, device to device, collaborative, and centralized. The