Cognitive radio (CR) is seen as a new approach to a more efficient utilization of natural resources - the radio electromagnetic spectrum. CR is described as an intelligent wireless communication system that is aware of your surroundings and to which it adapts own radio operating parameters. The most important function of cognitive radio is the detection of the spectrum, or spectral detection of free space. In this paper, the focus is placed on energy detection technique, by which we determine the status of the primary users (i.e. occupancy / availability of the spectrum), and the (centralized) cooperative detection range, within which it applies detection of energy together with the fusion of deciding where the data fusion is the process of combining local data detected, in order to make cooperative decisions. Optimal detection performance in such a co-operative detection of the spectrum is tested using MATLAB software package, with the aim of minimizing the total error of detecting a primary user.

Regular and systematic public transport is of great importance to all residents in any country, in the city and on commuter routes. In our environment, users of public transport can track the movement of vehicles with great difficulty, given that the current system does not meet the necessary criteria, and does not comply with the functioning of transport system. The aim of the final paper is to show the development of such a system using ZigBee and Arduino platforms. This paper shows an example of use the technologies mentioned above, their main advantages and disadvantages, with the emphasis on communication between the device and its smooth progress. In order to show the way in which the system could function, a simple mesh network was created, consisting of coordinator, routers for data distribution and end devices representing the vehicles. To view the results a web application was developed using open-source tool which is for display of the collected data on the movement of nodes in the network.

Abstract This paper discusses the problem of finding the optimal network topological configuration by changing the feeder status. The reconfiguration problem is considered as a multiobjective problem aiming to minimize power losses and total interruptions costs subject to the system constraints: the network radiality voltage limits and feeder capability limits. Due to its complexity, the metaheuristic methods can be applied to solve the problem and often the choice is genetic algorithm. NSGA II is used to solve the multiobjective optimization problem in order to get Pareto optimal set with possible solutions. The proposed method has been tested on real 35 kV distribution network. The numerical results are presented to illustrate the feasibility of the proposed genetic algorithm. Keywords radial distribution network, multiobjective optimization, reconfiguration, genetic algorithms, NSGA II