Tymoteusz Miller, G. Mikiciuk, Irmina Durlik
et al.
The integration of the Internet of Things (IoT) and artificial intelligence (AI) has reshaped modern agriculture by enabling precision farming, real-time monitoring, and data-driven decision-making. This systematic review, conducted in accordance with the PRISMA methodology, provides a comprehensive overview of recent advancements in smart sensing technologies for arable crops and grasslands. We analyzed the peer-reviewed literature published between 2020 and 2024, focusing on the adoption of IoT-based sensor networks and AI-driven analytics across various agricultural applications. The findings reveal a significant increase in research output, particularly in the use of optical, acoustic, electromagnetic, and soil sensors, alongside machine learning models such as SVMs, CNNs, and random forests for optimizing irrigation, fertilization, and pest management strategies. However, this review also identifies critical challenges, including high infrastructure costs, limited interoperability, connectivity constraints in rural areas, and ethical concerns regarding transparency and data privacy. To address these barriers, recent innovations have emphasized the potential of Edge AI for local inference, blockchain systems for decentralized data governance, and autonomous platforms for field-level automation. Moreover, policy interventions are needed to ensure fair data ownership, cybersecurity, and equitable access to smart farming tools, especially in developing regions. This review is the first to systematically examine AI-integrated sensing technologies with an exclusive focus on arable crops and grasslands, offering an in-depth synthesis of both technological progress and real-world implementation gaps.
Gintautas BUREIKA, Kristina VAIČIŪTĖ, Valerii SAMSONKIN
The level of technological innovation and the efficiency of transport logistics in enterprises principally depend on the resources that are used. The authors aim to develop a new approach to assess the interface between railway innovation implementation and the competencies of logistics specialists. The application of advanced technologies, such as digitisation and automation, substantially improves key performance indicators while simultaneously lowering operational costs for railway undertakings. There are notable advancements in technology within railway transport, with a particular emphasis on digitalisation. Analysis and research to determine specific engineering competencies of logistics specialists are highly anticipated and needed. This research focuses on the analysis and assessment of the interconnection between technological innovations in railway transport and the engineering competencies of logistics specialists. An analytic hierarchy process (AHP) method is used to assess the impact of technological innovations on the engineering competencies of logistics specialists, aiming to establish the presumed link between social psychological and technological factors. A new approach for assessing the competencies of logistics specialists in the railway sector has been developed. It is proven that the implementation of technological innovations within railway companies serves as the decisive factor driving the improvement of engineering competencies for logistics specialists.
ABSTRACT The rapid development of artificial intelligence (AI) and digitalization has increased the use of wearable flexible sensors in sports. The integration of new materials and artificial intelligence has markedly enhanced the monitoring and intelligent processing capabilities of these sensors, achieving substantial improvements in accuracy and response speed. However, these sensors still encounter challenges in complex environments, including optical interference, temperature fluctuations, humidity, and mechanical stability, which severely impact their monitoring performance. This article provides a comprehensive review of the latest advancements in artificial intelligence-assisted wearable flexible sensors for motion detection, focusing on the operational mechanisms, performance enhancements, and algorithm optimization of convolutional neural networks (CNN), temporal data modeling, multimodal fusion technology, and natural language generation. We also conducted in-depth analyses of the material preparation, artificial intelligence algorithm integration, and motion application development of wearable sensors based on optics, bioelectrochemistry, strain, and fabric. Finally, potential research directions and technological challenges for the future were also examined. Through interdisciplinary collaboration and innovation, intelligent sensors are anticipated to fully realize their potential in sports, healthcare, industrial automation, and other fields, thereby injecting new impetus into the development of intelligent technology. GRAPHICAL ABSTRACT
J. Ruiz-Vanoye, O. Díaz-Parra, M. A. Márquez Vera
et al.
The concept of Quality of Aquaculture Services (QoAS) is inspired by the Quality of Service (QoS) principle, originally developed in the field of networks and telecommunications, where it refers to the ability to guarantee the quality, availability, and priority of service in a communications system. Adapted to the aquaculture context, QoAS is fundamental to maximising the benefits of Integrated Multi-Trophic Aquaculture (IMTA). IMTA has emerged as a sustainable approach to meet the growing global demand for aquatic food products by combining species from different trophic levels in a single system, optimising resource use, improving environmental performance, and diversifying production. However, ensuring QoAS in these complex systems requires the implementation of advanced technologies to monitor, manage, and optimise every aspect of the aquaculture process. This article presents a comprehensive review of technologies applied at IMTA, focusing on IoT-based monitoring systems, resource management algorithms, water recirculation technologies, intelligent automation, biosecurity, and data management platforms. Our review finds that IoT and automation-based solutions significantly enhance real-time monitoring, increasing operational efficiency and environmental sustainability. Key challenges identified include integration complexity, high costs, and technical expertise requirements, but the ongoing development of modular, user-friendly solutions indicates a promising trajectory. This review highlights the transformative role of technological innovation in IMTA, providing a foundation for future research and advancements in QoAS management in aquaculture.
This study integrates quantitative scientometric analysis with a qualitative systematic review to comprehensively examine the evolution, core research themes, and emerging trends of three-dimensional (3D) visualization technology in architectural heritage conservation from 2005 to 2024. A total of 813 relevant publications were retrieved from the Web of Science Core Collection and analyzed using CiteSpace to construct a detailed knowledge map of the field. The findings highlight that foundational technologies such as terrestrial laser scanning (TLS), photogrammetry, building information modeling (BIM), and heritage building information modeling (HBIM) have laid a solid technical foundation for accurate heritage documentation and semantic representation. At the same time, the integration of digital twins, the Internet of Things (IoT), artificial intelligence (AI), and immersive technologies has facilitated a shift from static documentation to dynamic perception, real-time analysis, and interactive engagement. The analysis identifies four major research domains: (1) 3D data acquisition and modeling techniques, (2) digital heritage documentation and information management, (3) virtual reconstruction and interactive visualization, and (4) digital transformation and cultural narrative integration. Based on these insights, this study proposes four key directions for future research: advancing intelligence and automation in 3D modeling workflows; enhancing cross-platform interoperability and semantic standardization; realizing the full lifecycle management of architectural heritage; and enhancing cultural narratives through digital expression. This study provides a systematic and in-depth understanding of the role of 3D visualization in architectural heritage conservation. It offers a solid theoretical foundation and strategic guidance for technological innovation, policy development, and interdisciplinary collaboration in the digital heritage field.
Surfactants are chemical compounds present in a large number of products that people use on a daily basis, starting with detergents for washing clothes, dishes, personal hygiene products, etc. Some products also contain certain heavy metals. Their uses cause heavy contamination of wastewater that must be purified before discharge into receivers. Given that some types of surfactants are very persistent and heavy metals are non-biodegradable and toxic even in small concentrations, the purification process requires a complex approach and a combination of different methods. Bioremediation, as an environmentally acceptable and economically clean technology, has great potential. It is based on the use of indigenous microorganisms that have developed different mechanisms for breaking down and removing or detoxifying a large number of pollutants and are excellent candidates for bioremediation of wastewater. Bacteria can degrade surfactants as sole carbon sources and exhibit tolerance to various heavy metals. This paper summarizes the most significant results, highlighting the potential of bacteria for the biodegradation of surfactants and heavy metals, with the aim of drawing attention to their insufficient practical application in wastewater treatment. Bioreactors and microbial fuel cells are described as currently relevant strategies for bioremediation.
This study investigates the effects of formal and informal external factors on citizens’ intention to use DigiLocker, which is a government-backed cloud storage service (CSS). It also examines how trust in government moderates these effects. This research framework is grounded in institutional theory. The proposed model was validated by quantitative analysis of primary data collected through a survey in Delhi, the national capital region (NCR) of India.
The findings indicate that pressures can be divided into two categories — 1) formal (coercive pressure), and 2) informal (mimetic, and normative). Both significantly influence citizens’ attitudes, which in turn influence their intention to use DigiLocker. Moreover, coercive pressure has been found to be the strongest influencer of citizens’ attitudes. The moderating function of trust in the government has an ambiguous impact on different dimensions. That is, it is positive regarding the relationship between coercive pressures and citizens’ attitudes. At the same time it negatively moderates the relationships between mimetic and normative pressures and citizens’ attitudes. This study suggests that in order to effectively encourage the adoption of public CSSs, policymakers and service providers should consider the interplay of coercive, normative, and mimetic pressures along with trust.
Zdravko Šumić, Aleksandra Tepić Horecki, Lato Pezo
et al.
Dried peaches are widely consumed as a snack food product and used as an ingredient in cereals as well in chocolate and energy bars. Accordingly, the main objective of this investigation was to optimize the vacuum-drying process for peaches using a combination of three different statistical methods: principal component analysis, the standard score method and an artificial neural network approach. Applied input drying parameters were temperature (50–70 °C), pressure (20–120 mbar) and time (6–10 h), while the investigated output parameters were moisture content, water activity, total color change, phenolic and flavonoid contents and antioxidant activity. It was noted that all investigated output parameters constantly decreased (moisture content, water activity) and increased (total color change, total phenolic and flavonoid contents and antioxidant activity (FRAP, DPPH and ABTS assays)) in accordance with the applied drying temperature. The key variables accounted for 86.33% of data variance based on the PCA results, while the SS and ANN method resulted in the same optimal drying conditions: 60 °C, 70 mbar and 6 h, which indicated the effectiveness of the applied statistical methods.
This case study introduces personal branding as an innovation in Career and Life Design. While Life Design offers a roadmap for navigating complex career paths, it requires a deep understanding of one’s identity, values, and aspirations. Personal branding can be a valuable complement to Life Design, providing individuals with a structured process for self-discovery and expression. By integrating principles of identity theory, self-concept theory, and brand management into a curriculum focused on personal brand development, students are empowered to construct meaningful and fulfilling life paths. The findings described in this case study suggest that personal branding can serve as a powerful tool for self-discovery, career exploration, and overall life design. Future research should explore the long-term impacts of personal branding education on career outcomes and overall life satisfaction.
Ekaterina Chytilová, Jarmila Straková, Milan Talíř
The main aim of this article is to identify the evolution of the importance of supplier-customer relations in the period of crisis and the factors influencing the change of this importance. The research question was answered by testing a total of 6 hypotheses, which focused on comparing the degree of influence of factors such as firm size, industry, and profitability on the growth in the importance of supplier-customer relationships in the COVID-19 period. Boxplot and histogram were used to ensure the normality of data. The results suggest that the significance of supplier-customer relationships increased during the crisis period (COVID-19). The firm's profitability influences the growth in the importance of supplier-customer relationships before the pandemic, industry (the growth in importance is more pronounced in industrial firms) and overall sector (the growth in importance is stronger in the secondary sector than in the tertiary sector). In contrast, the association between firm size and the growth in the importance of supplier-customer relationships is not confirmed. Limitations of the study: the research results apply only to enterprises in the Czech Republic, and it is of a short-term focus (i.e., it cannot be said with certainty whether the increase in the importance of supplier-customer relationships is permanent or a short-term fluctuation). Thus, the results of the impact of individual factors may vary over longer time horizons.
Sustainability of fruit production is becoming a necessity in the time of climate changes and severe environmental issues, including decreasing water availability and biodiversity loss. To overcome these difficulties in sweet cherry production, we aimed to investigate the autochthonous cherry germplasm as a source of adaptable, size-controlling and productive rootstocks. The performance of sweet cherry cultivar ‘Summit’ grafted on six rootstock candidates and ‘Gisela 5’ as a control has been assessed in semi-arid climate, in conditions without irrigation and pruning, and with minimal herbicides’ application. The qualitative (anchorage, suckering, vitality), vegetative (trunk cross sectional area—TCSA, tree dimensions) and generative (potential and achieved yielding, fruit quality) characteristics were investigated. All candidates provided adequate anchorage while three candidates did not form suckers. Trees on ‘Gisela 5’ showed the lowest vitality. The scion TCSA in the fifth vegetation ranged from 16.7 to 47.2 cm2, while tree height, crown width and depth were up to 293, 150 and 175 cm, respectively. In sixth vegetation, the yield reached 4.1 kg. The average fruit mass in the trial of 2020–2021 was 8 g, fruit width was up to 27.5 cm, while the dry matter content reached 19%. The study showed that with the proper rootstock selection, sweet cherries could achieve satisfactory growth and yield without harming the environment and with minimal orchard’s maintenance practices. Within investigated autochthonous material, candidate PC_02_01/4 induced the best performance of ‘Summit’ cultivar.
One of the most recent trends in the global economy is the stigmatization of the global oil and gas industry, i.e., the sharply negative public perception of the industry as a whole, and of its key players in particular. These processes, directly related to the aggravation of the climate-related issues, have already become a source of substantial problems for major industry players. In recent years, public opinion regarding major international oil and gas corporations has changed markedly, at least in most Western countries. Global industry leaders (the so-called supermajors) are increasingly perceived as an existential threat to humanity, laying on them the main responsibility for global warming. Faced with the challenges of the industry-level public ostracism (industry stigma), these companies have been the first to develop a set of responses. This paper attempts to take a fresh look at the supermajors’ climate strategies for responding to the industry stigma. Looking through the prism of the stigma management concept helps one identify the reasons behind the changes in global oil and gas corporations’ relevant strategies in the course of their evolution, and understand the logic behind the different approaches to the green transformation employed by European and US supermajors.
Background: Intelligent monitoring of human action in production is an important step to help standardize production processes and construct a digital twin shop-floor rapidly. Human action has a significant impact on the production safety and efficiency of a shop-floor, however, because of the high individual initiative of humans, it is difficult to realize real-time action detection in a digital twin shop-floor. Methods: We proposed a real-time detection approach for shop-floor production action. This approach used the sequence data of continuous human skeleton joints sequences as the input. We then reconstructed the Joint Classification-Regression Recurrent Neural Networks (JCR-RNN) based on Temporal Convolution Network (TCN) and Graph Convolution Network (GCN). We called this approach the Temporal Action Detection Net (TAD-Net), which realized real-time shop-floor production action detection. Results: The results of the verification experiment showed that our approach has achieved a high temporal positioning score, recognition speed, and accuracy when applied to the existing Online Action Detection (OAD) dataset and the Nanjing University of Science and Technology 3 Dimensions (NJUST3D) dataset. TAD-Net can meet the actual needs of the digital twin shop-floor. Conclusions: Our method has higher recognition accuracy, temporal positioning accuracy, and faster running speed than other mainstream network models, it can better meet actual application requirements, and has important research value and practical significance for standardizing shop-floor production processes, reducing production security risks, and contributing to the understanding of real-time production action.
Juan J. Dolado, Florentino Felgueroso, Juan F. Jimeno
Purpose – This paper aims to review the experience so far of the Spanish labour market during the Covid-19 crisis in the light of the existing institutions, its performance during past recessions and the policy measures adopted during the pandemic. Emphasis is placed on the role of worldwide trends in labour markets because of automation and artificial intelligence, in shaping a potential recovery of this (hopefully) transitory shock through a big reallocation process of employment and economic activity. It also highlights some innovations to employment and social policies needed to smooth the reallocation process and lessen the rise in inequality associated to technological trends. Design/methodology/approach – Theory and empirics. Findings – The Spanish labour market will subject to a great reallocation shock as a result of Covid-19 and secular technological changes. Reforms need to be undertaken. Originality/value – An overview and some new results.