• Energy Research

Energy management in smart cities has gained particular significance in the context of climate change and the evolving geopolitical landscape. It has become a key element of sustainable urban development. In this context, energy management plays a central role in facilitating the growth of smart and sustainable cities. The aim of this article is to analyse existing scientific research related to energy in smart cities, identify technological trends, and highlight prospective directions for future studies in this field. The research involves a literature review based on the analysis of articles from the Scopus and Web of Science databases to identify and evaluate studies concerning energy in smart cities. The findings suggest that future research should focus on the development of smart energy grids, energy storage, the integration of renewable energy sources, as well as innovative technologies (e.g., Internet of Things, 5G/6G, artificial intelligence, blockchain, digital twins). This article emphasises the significance of technologies that can enhance energy efficiency in cities, contributing to their sustainable development. The recommended practical and policy directions highlight the development of smart grids as a cornerstone for adaptive energy management and the integration of renewable energy sources, underpinned by regulations encouraging collaboration between operators and consumers. Municipal policies should prioritise the adoption of advanced technologies, such as the IoT, AI, blockchain, digital twins, and energy storage systems, to improve forecasting and resource efficiency. Investments in zero-emission buildings, renewable-powered public transport, and green infrastructure are essential for enhancing energy efficiency and reducing emissions. Furthermore, community engagement and awareness campaigns should form an integral part of promoting sustainable energy practices aligned with broader development objectives.

Abstract The influence of artificial intelligence (AI) in smart cities has resulted in enhanced efficiency, accessibility, and improved quality of life. However, this integration has brought forth new challenges, particularly concerning data security and privacy due to the widespread use of Internet of Things (IoT) technologies. The article aims to provide a classification of scientific research relating to artificial intelligence in smart city issues and to identify emerging directions of future research. A systematic literature review based on bibliometric analysis of Scopus and Web of Science databases was conducted for the study. Research query included TITLE-ABS-KEY (“smart city” AND “artificial intelligence”) in the case of Scopus and TS = (“smart city” AND “artificial intelligence”) in the case of the Web of Sciences database. For the purpose of the analysis, 3101 publication records were qualified. Based on bibliometric analysis, seven research areas were identified: safety, living, energy, mobility, health, pollution, and industry. Urban mobility has seen significant innovations through AI applications, such as autonomous vehicles (AVs), electric vehicles (EVs), and unmanned aerial vehicles (UAVs), yet security concerns persist, necessitating further research in this area. AI’s impact extends to energy management and sustainability practices, demanding standardised regulations to guide future research in renewable energy adoption and developing integrated local energy systems. Additionally, AI’s applications in health, environmental management, and the industrial sector require further investigation to address data handling, privacy, security, and societal implications, ensuring responsible and sustainable digitisation in smart cities.

Production of food-grade emulsions is continuously rising globally, especially in developing countries. The steepest demand growth is in the segment of inexpensive meat products where edible emulsions serve as lubricants to mitigate economic loses linked with mechanical damage during automated processing of artificial casings. Provided that production goal is to minimize emulsion transfer into the product, its vast majority becomes voluminous greasy and sticky waste. Public sewage treatment plants cannot process such waste, its cleaning processes tends to collapse under loads of emulsions. To make matters worse, composition of emulsions often changes (according to actual pricing of main components) and emulsion manufacturers carefully guard their recipes. Therefore, running of in-house sewage plants would require continuous experimentation linked with need for skilled personnel, frequent changes in technology setup and high operating costs in general. Consequently, it was repeatedly and independently reported that emulsion waste is poured onto wildlife, resulting in environmental damage and an intense rotting odor. Three new methods of emulsion breakdown are proposed and techno-economically assessed. High versatility of methods was confirmed and multiple austerity measures were incorporated. Emulsions are also assessed in terms of an energy source for aerobic and anaerobic microorganisms. It is reported that the addition of edible emulsion to compost does not result in increased product quality or cost reduction. It is firstly revealed that edible emulsions can instantly create an anaerobic environment and accelerate biogas production through the formation of surface films on feedstock surface. Adding waste food-grade emulsions to the biogas plant makes it possible to 100% reduce process water consumption in biogas stations as the process speed can be shortened by approximately 12%.

Considerable research attention has focused on the labor market impacts of immigration, the operation and competitiveness of the European Union (EU) labor market, and the expenditures and advantages of labor circulation for sending and receiving economies. The aim of the present study is to examine and evaluate the negative social consequences arising from the mobility of workers, the social and economic drivers of migration, and the effect of immigration on natives’ labor market results such as wages and employment.

This study aims to examine the expansion of the electric vehicle fleet in the context of transport electrification in the European Union. We assessed the car market, following demand and sales trends for electric and hybrid cars. It was explored the possibility of a causal relationship among the percentage of BEV + PHEV in the total fleet and purchasing power, loading infrastructure, government support, the level of education and the degree of digitalization. To achieve the main objectives of the research to assess the existence and magnitude of the causal effects of the considered variables on the percentage of BEV + PHEV in the total fleet, we conducted a cross-sectional analysis in 2020 among the European Union (EU) countries. Five research hypotheses were formulated and tested. The results confirmed that the economic and social development of a region, the charging infrastructure, the government support measures, and the degree of digitalization positively influence the desire of the EU population to buy electric cars.

Prediction of the financial difficulties of companies has been dealt with over the last years by scientists and economists worldwide. Several prediction models mostly focused on a particular sector of the national economy, have been created also in Slovakia. The main purpose of this paper is to create new prediction models for small and medium-sized companies in Slovakia, based on real data from the Amadeus database from the years 2016–2018. We created prediction models of financial difficulties of companies for 1 year in advance and also a model for 2 years prediction. These models are based on the combination of two methods, discriminant analysis and logistic regression that belong, among others, to the group of the most commonly used methods to derive prediction models of financial difficulties of the companies. The overall prediction powers of the combined model are 90.6%, 93.8% and 90.4%. The results of this analysis can be used for early prediction of the financial difficulties of the company, that could be very useful for all the stakeholders.

This paper presents a heuristic methodology for estimating the possible variation of the liquid biofuel potential of a region, an appraisal made for a future period of time. The determination of the liquid biofuel potential has been made up either on the account of an average (constant) yield of the energetic crops that were used, or on the account of a yield that varies depending on a known trend, which can be estimated through a certain method. The proposed methodology uses the variation of the yield of energetic crops over time in order to simulate a variation of the biofuel potential for a future ten year time period. This new approach to the problem of determining the liquid biofuel potential of a certain land area can be useful for investors, as it allows making a more realistic analysis of the investment risk and of the possibilities of recovering the investment. On the other hand, the presented methodology can be useful to the governmental administration in order to elaborate strategies and policies to ensure the necessity of fuels and liquid biofuels for transportation, in a certain area. Unlike current methods, which approach the problem of determining the liquid biofuel potential in a deterministic way, by using econometric methods, the proposed methodology uses heuristic reasoning schemes in order to reduce the great number of factors that actually influence the biofuel potential and which usually have unknown values.

This article proposes a synthetic analysis of the development level of regions in Romania with the concentration/diversification model, using Gini coefficients and Lorenz curve, based on the current statistical indicators. Knowing the degree of concentration and also the influence factors is useful in making decisions and setting regional policy measures. The analysis of regional disparities based on a series of data and indicators provided by The Romanian National Institute of Statistics for 2007–2016. The main findings highlight a deepening of the regional disparities in Romania in 2016 compared with 2007 explained mainly by the fact that the Bucharest–Ilfov region registered an economic development much above the other regions.