Home automation systems have attracted considerable attention with the advancement of communications technology. A smart home (SH) is an Internet of Things (IoT) application that utilizes the Internet to monitor and control appliances using a home automation system. Lack of IoT technology usage, unfriendly user interface, limited wireless transmission range, and high costs are the limitations of existing home automation systems. Therefore, this study presents a cost-effective and hybrid (local and remote) IoTbased home automation system with a user-friendly interface for smartphones and laptops. A prototype called IoT@HoMe is developed with an algorithm to enable the monitoring of home conditions and automate the control of home appliances over the Internet anytime and anywhere. This system utilizes a node microcontroller unit (NodeMCU) as a Wi-Fi-based gateway to connect different sensors and updates their data to Adafruit IO cloud server. The collected data from several sensors (radio-frequency identification, ultrasonic, temperature, humidity, gas, and motion sensors) can be accessed via If This Then That (IFTTT) on users' devices (smartphones and/or laptops) over the Internet regardless of their location. A set of relays is used to connect the NodeMCU to homes under controlled appliances. The designed system is structured in a portable manner as a control box that can be attached for monitoring and controlling a real house. The proposed IoT-based system for home automation can easily and efficiently control appliances over the Internet and support home safety with autonomous operation. IoT@HoMe is a low cost and reliable automation system that reduces energy consumption and can notably provide convenience, safety, and security for SH residents.

Urbanization and increased building density of cities are essential features of modern society. Not only does such a way of life bring economic benefits, but it also poses a new set of problems for city authorities. One of these problems is efficient traffic management and analysis. High population density leads to the tremendous number of personal cars, an increased number of freight vehicles for transportation of commodities and goods, tight pedestrian traffic. Transportation tasks can no longer be addressed by sub-optimal heuristics, based on the small amount of the manually gathered statistics. To make efficient decisions, forecast and assess their consequences, authorities require an automated system for analyzing traffic flow throughout the city. Nowadays, many cities have low-cost video surveillance systems, also known as closed-circuit television (CCTV). They exhibit rapid growth nowadays and usually include heterogeneous cameras with various resolution, mounting points, and frame rates [43]. CCTV works 24 h a day, 7 days a week and generates a massive amount of information, called Big Data. Among other applications, this data can serve as a foundation for the automated traffic surveillance system.

Failures of friction bearings of the crank mechanism comprise from 5 to 25 % of engine failures. The analysis of the main reasons for failures shows that the dominant reasons are the following: excess of loading conditions; severe operating conditions; non-observance of the periodic maintenance of the lubrication system; violation of the procedure and conditions of maintenance (contamination, oil residues, etc.); use of poorquality oils and filters, etc. It is possible to prevent the growth of failures of friction bearings by a continuous monitoring of their complex technical state. For that purpose, we have supposed that the technical state of the crankshaft main bearings of the crank mechanism can be determined by measuring the pressures in the central oil line and calculating their difference in the cycles with the maximum load and without it at different engine crankshaft rotation frequency. As a result of the experimental work, we developed a method for in-place diagnostics of the state of friction bearings of the internal combustion engine, as well as an instrument that provides loading conditions for the bearings of the crank mechanism. We obtained an experimental dependence for determining the wear degree of the crankshaft main journal by the difference in the minimum pressure amplitudes of two adjacent cycles during the operation of the diagnosed cylinder in various modes.

In many cities of the world, the problem of traffic congestion on the roads remains relevant and unresolved. It is especially noticeable at signal-controlled intersections, since traffic signalization is among the most important factors that reduce the maximum possible value of the traffic flow rate at the exit of a street intersection. Therefore, the development of a methodology aimed at reducing transport losses when pedestrians move through signal-controlled intersections is a joint task for the research and engineering community and municipalities. This paper is a continuation of a study wherein the results produced a mathematical model of the influence of lane occupancy and traffic signalization on the traffic flow rate. These results were then experimentally confirmed. The purpose of this work is to develop a method for the practical application of the mathematical model thus obtained. Together with the obtained results of the previous study, as well as a systems approach, traffic flow theory, impulses, probabilities and mathematical statistics form the methodological basis of this work. This paper established possible areas for the practical application of the previously obtained mathematical model. To collect the initial experimental data, open-street video surveillance cameras were used as vehicle detectors, the image streams of which were processed in real time using neural network technologies. Based on the results of this work, a new method was developed that allows for the adjustment of the traffic signal cycle, considering the influence of lane occupancy. In addition, the technological, economic and environmental effects were calculated, which was achieved through the application of the proposed method.

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Vehicular network is a communication technology designed to provide comfort and improve life safety and driving efficiency on the road. In vehicular network, trustworthy communication is very important as fake applications may lead to disastrous road accidents. Several information hiding methods are used to enable vehicles to communicate secretly or to covertly report a misbehaving vehicle. The work in this paper focuses on a performance analysis based on 2-D Markov chain model for the system throughput of steganographic scheme in relation to the IEEE 802.11p standard. This model studies wireless padding (WiPad) that is used to hide data into the padding of packets at the physical layer of wireless local area networks (WLANs). The analytical study is under non-saturated conditions with non-ideal transmission channel. The study also considers the rate of packet arrival with the first order of buffer memory, back-off timer freezing, back-off phases, and short retry limit to satisfy the IEEE 802.11p specifications. It emphasizes that taking these factors into account are significant in modelling the system throughput of the steganographic channel. These factors typically provide a precise channel access estimation, yield more accurate findings of system throughput, use the channel efficiently, prevent overestimation of saturation throughput, and ensure that no packet is served indefinitely. The model is validated by comparing the numerical and simulation results under different network parameters. Analytical and simulation results stated that the values of the system throughput of the steganographic channel based on data and control frames are low as the vehicles number n, traffic arrival rate λ, packet size, and the value of Bit Error Rate (BER) increase. INDEX TERMS Vehicular network, IEEE 802.11p, steganographic channel, non-ideal transmission channel, BER.

Currently, in many cities around the world there is a significant increase in the number of vehicles, which leads to an aggravation of problems and contradictions in the road and transport system. This is especially true of traffic congestion, since the presence of the congestion leads to a number of negative consequences: an increase in travel time, additional fuel consumption and vehicle wear, stress and irritation of drivers and passengers, environmental poisoning and others. To solve the problem of congestion, it is necessary to have a reliable system for collecting information about the situation on the roads and a well-developed method for analyzing the collected information. The paper discusses the possibilities of collecting the required information using multi-touch video cameras and ways to improve them. A distinctive feature of this study is the registration of pedestrians crossing the road at the intersection. The aim of the work is to develop methods for collecting information using road sensor video surveillance systems in a traffic congestion and data processing using statistical methods such as: multiple regression analysis, cluster analysis, multidimensional scaling methods and others. The tasks were set: 1) to identify the most significant factors affecting the intensity of movement of vehicles at intersections in a congestion; 2) divide congestion into clusters with the identification of their characteristics; 3) to give a visual representation of multidimensional statistical information obtained with the help of multi-touch road video cameras.

The possibilities of collecting the necessary information using multi-touch cameras and ways to improve road traffic data collection are considered. An increase in the number of vehicles leads to traffic jams, which in turn leads to an increase in travel time, additional fuel consumption and other negative consequences. To solve this problem, it is necessary to have a reliable information collection system and apply modern effective methods of processing the collected information. The technology considered in the article allows taking into account pedestrians crossing the intersection. The purpose of this article is to determine the most important traffic characteristics that affect the traffic capacity of the intersection, in other words, the actual number of passing cars. Throughput is taken as a dependent variable. Based on the results of the regression analysis, a model was developed to predict the intersection throughput taking into account the most important traffic characteristics. Besides, this model is based on the fuzzy logic method and using the Fuzzy TECH 5.81d Professional Edition computer program.