For the premium calculation and billing process in the motor insurance, current billing models are very general and not optimally tailored for the end users. Important parameters such as mileage, driving behavior and types of roads driven are not considered for the premium calculation. Development of advanced information and communication systems, significant drop in the technology cost of ownership, as well as the necessity for market differentiation in the insurance industry, facilitated the appearance of new billing models in the motor insurance industry. The purpose of this paper is to demonstrate underlying principles of the technology facilitating new billing models in the motor insurance industry. This paper gives an overview of the system architecture of one of the telematics systems offered and used on the market, as well as the data model used in the billing process. The potential of such a system is demonstrated through the real case project implemented in Eastern Europe

Detection of DDoS (Distributed Denial of Service) traffic is of great importance for the availability protection of services and other information and communication resources. The research presented in this paper shows the application of artificial neural networks in the development of detection and classification model for three types of DDoS attacks and legitimate network traffic. Simulation results of developed model showed accuracy of 95.6% in classification of pre-defined classes of traffic.

The ability to recognize human speech has always been an area of interest of people primarily because of the large range of applications in almost every segment of society. The development of science and technology made visible improvements in the capabilities and the quality of recognition of the human voice/speech using some kind of terminal devices. Speech recognition enables devices to adapt voice information in understandable form, which means complete identification and understanding of information. The primary purpose of recognizing of human speech is the ability to customize information (which are intended to people) for using with devices. The aim of voice recognition systems is to provide links and ease of communication between the device and the man and the development of further possible applications. Given the current trends in the use of smart terminal devices and technical and technological opportunities that they offer, it is inevitable to study the potential of these devices in the area of human voice recognition. The purpose of the paper is to show the possibilities of human voice recognition using smart terminal devices. Furthermore, all of this will be analyzed primarily in the transport(car) environment with emphasis on the potential advantages and disadvantages of such tools and principles

The availability of information and communication (IC) resources is a growing problem caused by the increase in the number of users, IC services, and the capacity constraints. IC resources need to be available to legitimate users at the required time. The availability is of crucial importance in IC environments such as smart city, autonomous vehicle, or critical infrastructure management systems. In the mentioned and similar environments the unavailability of resources can also have negative consequences on people's safety. The distributed denial of service (DDoS) attacks and traffic that such attacks generate, represent a growing problem in the last decade. Their goal is to disable access to the resources for legitimate users. This paper analyses the trends of such traffic which indicates the importance of its detection methods research. The paper also provides an overview of the currently used approaches used in detection system and model development. Based on the analysis of the previous research, the disadvantages of the used approaches have been identified which opens the space and gives the direction for future research. Besides the mentioned this paper highlights a DDoS traffic generated through Internet of things (IoT) devices as an evolving threat that needs to be taken into consideration in the future studies.

The methods of measuring driving behaviour and the quality of drive in road transport are important factors in data acquisition and subsequent analysis of driving. The prevalence of smart terminal devices and cost effectiveness of On-Board Diagnostics (OBD) sensor devices provide great potential and the availability of the aforementioned technologies. This study shows the possibility of using information and communication technologies (ICT) and sensor devices for measuring the effectiveness of eco-driving. The ease of implementation of ICT elements, the accuracy of collected data and their storage for later data analysis offer a number of possibilities to use. This study shows the technical solution of the system and analysis of collected data on actual driving samples. By comparing normal and eco-driving modes, the advantage of using eco-driving modes is demonstrated through reduced fuel consumption and CO2 emissions amounting to almost 23% and 31%, respectively.