This article gives a review of modern networking technologies and standards used in the development of distributed control systems. Study of related scientific and professional literature has been performed, and basing on it a multi-level model of digital network structure in the field of small-scale autonomous combined power systems has been proposed. Necessity of integration of autonomous powering into SmartHouse systems and related distributed computing and networking issues are reflected as well. As there is a wide variety of industrial networking standards used, this review covers and groups more frequently used protocols and stacks from the view of OSI (Open Systems Interconnection) reference model and layers of industrial automation. The aim of this article is to give a reference-point in the development of distributed control systems in the field of small-scale autonomous power supply and integration of them in SmartHouse systems.

Nowadays all engineering technologies are based on the automation, but still there are some processes that are not easy to automate. One of them is the heating process using solid fuel boilers. The paper deals with automated double-link air flow control of the combustion process. The research target was to find more effective solutions of furnace air flow regulation to improve the combustion process efficiency. The research object was a 56 kW wood briquettes water heating boiler. The results of the experiment research show a higher efficiency of the combustion process with double-link air flow PI control using motor valves.

The research was conducted with the aim of studying the possibility of using automatic feeding stations for individual sheep (Ovis aries) feeding. The research was organized in 3 periods, in which 10–13 months old sheep – female only (1st research period), 6–10 months old sheep – female only (2nd research period) and 8–12 months old sheep – female only (3rd research period) were used. Part of the sheep did not visit the feeding station at all. Sequentially, over the research periods the percentage was 13%, 37% and 49%. Upon setting the concentrate daily ration 400 g per sheep, on the average the number of visits to the particular feeding station was 6.1 and 4.7 (sequentially in the 1st and 2nd research period). Upon increasing the concentrate ration amount up to 700 g per day, the average number of feeding station visits was 6.9 (in the 3rd research period). The number of visits to the automatic feeding station was varied (V is greater than 10%). Over the research period live weight of the sheep increased significantly (p ≤ 0.05) for the subgroups of animals which made visits to the feeding station regularly during the entire research period. In all research periods, the average daily concentrate intake (373.5 g in the 1st research period, 333.1 g in the 2nd research period and 581.2 g in the 3rd research period) was 93%, 83% and 83% respectively, of the maximum established feeding standard.

The authors explore ways to combine the use of traditional and mobile positioning data (as Big Data) in assessing the economic impact (EI) of tourism in specific regional areas in line with the opportunities of the digital age. In order to provide an automated evaluation of the tourism EI, a study is being carried out resulting in technical development of a prototype for two interconnected digital applications – ‘Data Bank’ and ‘Data Analysis’ – as a unified solution for research in the e-environment. The study is based on the research work started in 2017 that resulted in the development of a theoretical strategic model for the construction of the prototype. Continuing the research, the aim of this publication is to develop a theoretical tactical (technological action) model needed for the practical development of the prototype, incl. for the identification of prerequisites to develop the Software Design Description (SDD) of the prototype. To this end, the technological capabilities and their collaborative effects have been investigated in line with the requirements included in the prototype Software Requirements Specification (SRS). Performing the qualitative research, the tactical model has been developed, which designates the practical construction of the prototype. It consists of a combination and joint operation of 4 platforms (servers) – Apache Ambari, Apache Hadoop Ecosystem, Drupal and Jupyter Notebook. The strengths of the model, the risky features as well as the future perspectives for the practical implementation of the goal have been discovered during the research.

The model of automation and extension of tourism economic impact assessment in specific regions Tourism is measured by the statistics of visitor movements, expenditure and estimates of the number of visitor facilities. In the world there are many current tools, methodologies and innovative technologies used to measure the economic impact of tourism. Tourism statistics have been on the frontline of Big Data-related innovations of statistical sources and methods. Data from mobile phones (as part of Big Data set) are increasingly used as new indices for social science research. Therefore, this paper looks for an answer to the question – what is the specific of a theoretical model for automation tourism economic impact assessment in specific regions via the use of ICT and mobile positioning data (MPD)? Using qualitative research methods authors propose theoretical model based on two interlinked parts. First of which – ‘Data storage’ – can be built upon the most popular BD platform ‘Apache Hadoop Ecosystem’, where the data precision of the online surveys can be increased by implementing mobile positioning solutions. Meanwhile the other part – ‘Data analysis’ – can be based on the locally created assessment methodology, which has been derived from the Finnish standardized economic impact estimation approach. The research results show the findings and propose a theoretical model. Its strength and novelty lies in the ability to use traditional tourism statistics, the economic impact analysis and passive mobile positioning data for spatial characteristics of tourism flow. Its construction is a distinctive combination of typically used technological approaches.

This study is based on the authors’ research started in 2017 that resulted in the development of theoretical strategic and tactical models for the construction of a prototype for automated assessment of tourism economic impact in specific regions, including regions of national parks (NP), as well as for other studies. The aim of the research was testing the performance of the prototype in a research e-environment using the travellers’ survey data obtained in a study in 2019 on the national parks’ target groups (visitor behaviour) during the Gauja National Park (GNP) Travellers’ Days. The prototype was based on the open-source platform Drupal, MySQL used as a database management system (DMS). Drupal united with the Jupyter Notebook platform. The methodological substantiation of the test study is based on aspects of consumer behaviour. A quantitative study with details of qualitative research has been performed. Simple data sampling was used in the data acquisition, but in the analysis – induction, deduction approach, synthesis, data sorting and segmentation, determination of mean values and their expression in proportion; a comparative analysis was performed and conclusions characterizing the sample were made. After completing the prototype performance testing, the authors’ main findings indicate that the prototype’s performance efficiency in terms of time consumption is 23.3 times higher than equivalent work in MS Excel. The prototype has yielded quantitative results from the calculations, and that allows the formulation of the GNP’s Travellers’ Days visitor profile, which is characterized by a sample of the surveys.

The study aims to find out the efficiency of periodic training of the harvester (cut-to-length) operator, using the automatically saved data of the harvesterʼs information system. It has been established that logging service providers and training institutions do not analyse the operatorʼs work before starting the training; therefore, the training is carried out according to certain, standard programs, without going into the previous performance of each trainee operator. The research uses data automatically saved by Ponsse harvesters during the year, obtained from Ponsse Manager. The study found that by using automatically saved data of the harvester information and performing data grouping with subsequent analysis, it is possible to determine the progress in the execution of specific stem processing operations and to identify operations where the instructor should pay increased attention during training. The research analysed the data of 3 operators, obtained while working with Ponsse harvesters in clear-cutting. In the study, it was found that operator A reduced stem processing time by 3%, labour productivity increased by 15%, and fuel consumption per l m⁻³ decreased by 14% over 3 months. Operator B, after training, saw a 20% reduction in stem processing time, a 13% increase in work productivity, and a 5% increase in fuel consumption l m⁻³ over 3 months. Operator C had a 10% increase in stem processing time, a 1% increase in labour productivity, and a 2% increase in fuel consumption l m³ after training.

Robotic process automation (RPA) is relatively new software technology that is quickly being adopted by companies around the globe to free office workers from routine, monotonous and rule-based tasks letting them invest their time in higher complexity and value tasks. While big companies have money, time and workforce resources to implement RPA, small and medium enterprises (SME) fall behind in their effort to start using RPA despite the fact that for this segment of organizations RPA would be useful as it presents the opportunity to re-arrange their limited resources and delegate part of work to software. To address this situation, the aim of this paper is to conduct systematic review of literature regarding RPA appliances in enterprises in order to find out how to implement RPA successfully, what processes to give to RPA, and how SMEs can implement RPA better. During the review main guidelines on how to implement RPA in enterprise in general and which processes to delegate to RPA in particular were identified as well as challenges RPA implementation might bring to company. It was also noted that there is missing research on how to adopt RPA specifically in SMEs segment. The conclusion is that SMEs aimed RPA implementation guidelines are missing.

The algorithm is designed to improve the production of power lines, to forecast emergency situations and to recognize possible ecological risks.