This article presents a comparative analysis of two prominent machine learning techniques for predicting electricity consumption in workplace lighting systems: polynomial regression analysis and artificial neural networks. The primary objective is to assess their suitability and applicability for developing an accurate predictive model. After a brief overview of the current state of energy-saving techniques, the article examines several established models for predicting energy consumption in buildings and systems. These models include artificial neural networks, regression analysis and support vector machines. It then focuses on a practical comparison between polynomial regression analysis and an artificial neural network-based model. The article then looks at the data preparation process, outlining how the data is used within each model to establish appropriate prediction functions. Finally, it describes the methods used to evaluate the accuracy of the developed prediction functions. These functions allow the prediction of lighting consumption based on external lighting intensity. The article evaluates the accuracy of the developed prediction functions using the root mean square error, correlation coefficient and coefficient of determination values. The article compares these values obtained for both models, allowing a conclusive assessment of which model provides superior accuracy in predicting lighting consumption based on external lighting intensity.

The essential component of all the control and sensory systems is a communication layer. The MODBUS protocol used in automation and sensory industry defines a simple format of communication using the master/slave principle, although since it originated in the 1970s it has become obsolete. In this article is presented uBUS protocol as an enhancement of the MODBUS protocol uBUS protocol proposal brings advanced features for today’s requirements for embedded applications. Enhancements include address extension to 4079 addresses, adding a new communication mode (group broadcast), delegating selected master features to slave, linking with other communication interfaces and securing communications layer. The main part of the article deals with the description of design and implementation of the uBUS communication security. An RSA algorithm that uses asymmetric encryption was used to implement communication encryption. The article presents a way of implementing such encryption and its effectiveness on various types of microcontrollers implementing uBUS slaves. Since the communication protocol security is designed as a separate layer, it is possible to implement different types of encryption.

The Žilina airport was after almost 50 years of use measured by non-invasive methods including GPR and Profilograph GE in order to investigate the quality of the runway pavement at the chosen spots. Since it was just a pilot action, a sample of survey was carried out. The testing spots were placed where the geologic drill core J02 have been drilled out. The measurements performed by Profilograph GE were used to verify the quality of the pavement surface in term longitudinal unevenness by means of index IRI and C. The GPR survey was performed in 3D geometry, hence in the x - and y -direction. A horn type antenna with central frequency of 2 GHz was used on the test field in order to verify the thicknesses of pavement construction layers. Here, the result of a 3D survey is presented. The investigation confirms two sub-horizontal construction layers of the runway pavement. In some areas the GPR interpretation was not possible due to the signal attenuation. This significant signal attenuation is found mainly in the areas where the linear cracks are situated.

Currently, we are experiencing an ever-increasing demand for high-quality transportation in the distinctive natural environment of forest roads, which can be characterized by significant weather changes. The need for more effective management of the forest roads environment, a more direct, rapid response to fire interventions and, finally, the endeavor to expand recreational use of the woods in the growth of tourism are among the key factors. A thorough collection of diagnostic activities conducted on a regular basis, as well as a dataset of long-term monitored attributes of chosen sections, are the foundations of successful road infrastructure management. Our main contribution to this problem is the design of a probe for measuring the temperature profile for utilization in stand-alone systems or as a part of an IoT solution. We have addressed the design of the mechanical and electrical parts with emphasis on the accuracy of the sensor layout in the probe. Based on this design, we developed a simulation model, and compared the simulation results with the experimental results. An experimental installation was carried out which, based on measurements to date, confirmed the proposed probe meets the requirements of practice and will be deployed in a forest road environment.

Ensuring the sustainability of road infrastructure cannot be achieved without the continuous application of new knowledge and approaches within individual management steps. A particularly risky stage in the life cycle of existing roads is the operation phase. High attention is paid to the environmental, financial and social impacts and benefits of individual processes applied by road managers. These processes meet in pavement management systems (PMS), which, however, cannot work reliably without the necessary input data. Information on the development of the technical condition of the road can also be included among the most important data. The paper brings the first outputs from several years of research of measurements on the Slovak 1st class road. Its aim is to gradually determine the degradation functions for the needs of Slovak geographical, climatic and transport conditions. The secondary objective is to verify the reliability of non-destructive measurement procedures of the technical condition of the road. Emphasis is placed on the application of such mathematical procedures that can not only reliably bring about the determination of past developments in the roadway, but can also present the expected picture of future developments.

A considerable funds is spent for the roads maintenance in large areas during the winter. The road maintenance is significantly affected by the temperature change of the road structure. In remote locations may occur a situation, when it is not clear whether the sanding is actually needed because the lack of information on road conditions. In these cases, the actual road conditions are investigated by a personal inspection or by sending out a gritting vehicle. Here, however, is a risk of unnecessary trip the sanding vehicle. This situation is economically and environmentally unfavorable. The proposed system solves the problem of measuring the temperature profile of the road and the utilization of the predictive model to determine the future development trend of temperature. The system was technically designed as a set of sensors to monitor environmental values such as the temperature of the road, ambient temperature, relative air humidity, solar radiation and atmospheric pressure at the measuring point. An important part of the proposal is prediction model which based on the inputs from sensors and historical measurements can, with some probability, predict temperature trends at the measuring point. The proposed system addresses the economic and environmental aspects of winter road maintenance.