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The growing interest in the development of artificial intelligence (AI) agents is increasingly influencing socially significant domains such as public administration, education, and government services. In these areas, AI systems are expected to achieve high standards of performance, including accuracy, reliability, and contextual awareness, in order to support administrative processes and provide citizens with fast and dependable access to information. For this reason, selecting an appropriate model conception is...

Developing effective artificial intelligence agents requires more than selecting an appropriate language model. Agent performance is fundamentally constrained by the quality, structure, and accessibility of the underlying knowledge, making curated, continuously updated knowledge bases a core architectural component. While large language models, reasoning-oriented models, and research-focused models provide distinct capabilities for language understanding, reasoning, and summarisation, their practical effectiveness...

This article presents a technological approach to extract and combine data from government websites to facilitate access to disparate information and obtain valuable analysis on it in response to user queries. The study addresses the challenges of extracting information from complex government sources, which often contain regulatory documents in various formats. The lack of open access complicates data consolidation, leading to fragmented search and analysis processes. Data scraping is proposed as a solution, but ...

Artificial intelligence (AI) is rapidly penetrating all forms of digitised systems and services, including organisational, social, economic, and governmental, revolutionising the way information is processed, and decisions are made. The integration of AI in socially relevant areas is increasingly essential due to the growing use of digital services and the extensive, fragmented information spread across platforms. The lack of a unified approach to processing this data creates challenges in accessibility, reliabili...

Data collection and storage are crucial in the development of artificial intelligence (AI) within the socially relevant areas. Despite the increasing volume of information, it is often scattered across various sources, formats, and platforms, making effective analysis and application challenging. The lack of a unified framework for data integration further complicates efforts to leverage AI for informed decision-making, policy formulation, and public service optimisation. This article proposes a structured methodo...

The growing need for a sustainable and climate-resilient future places green energy and digital transformation at the heart of the European Union-s long-term strategic plan. Policies such as the European Green Deal and the Digital Europe Programme envisage a synchronised "twin transition", one that aims to decarbonise the economy and modernise its digital infrastructure simultaneously. While significant attention has been directed towards centralised digital solutions and large-scale grid management systems, less ...

Livestock barns are integral to modern agriculture, providing essential environments for raising animals. The air quality in these barns directly impacts livestock health, quality of production and environmental sustainability. Trends in key metrics such as gas concentrations, particulate matter levels, humidity content, and temperature can influence the overall health of livestock, barn operations, and broader ecological factors. Understanding these trends and their interrelationships is crucial for managing barn...

This article presents a study focused on animal activity recognition using a combination of IoT devices and signal processing techniques. The study involves collecting data from IoT devices placed on the cow's neck, which are equipped with an accelerometer and gyroscope, along with a synchronized video camera. The objective is to accurately recognize and classify four key activities exhibited by the cow. To prepare the collected signals for analysis, various signal processing techniques are applied. This includes ...

The continuous rise in global population necessitates the prediction of food resources, among which milk stands out as one of the staples. Dairy farms and processing plants need to know how much milk they will have available to manage their storage and processing capacities efficiently. Overestimating production can lead to wastage, while underestimating can lead to shortages. Knowing the expected milk quantity helps in planning the transportation, processing, and distribution of milk and milk products. This study...

This paper focuses on recognizing the activity of dairy cows using a non-invasive approach that monitors four key behaviors: licking, feeding, standing, and lying. The study used IoT devices with accelerometers and gyroscopes attached to the cow's neck to continuously monitor its movements. The data collection process aimed to capture the dynamic and static nature of dairy cow behaviors, providing a valuable data set for subsequent analysis. To efficiently process the raw data, we analyzed it and then used long sh...

The development of modern dairy farming is aimed at creating larger farms with more intensive production in accordance with the market needs. New larger livestock facilities need new approaches to management and logistics. The Internet of Things (IoT), machine learning (ML) and cloud computing are forming the basis of digital animal husbandry as they are increasingly being introduced into dairy farming. The collection of IoT sensor data and their storage in the information cloud allows the use of machine learning ...

Digital Twins can be seen as powering the next generation of IoT-connected solutions. Digital Twins model the real world by using historical and real-time data to represent the past and present and simulate the predictable future. Digital twins are related to a set of concepts such as digital representation and 3D visualization, integration, monitoring, control, computation, prediction, and decision-making. They are digital replicas of physical objects having bidirectional data flow. The physical object and its di...

The technological progress naturally leads to a transition from Agriculture 4.0 to Agriculture 5.0, which includes key technologies as Wireless Sensor Networks, Internet of Things, Cloud age, Artificial Intelligence, and Machine Learning accompanying agronomic activities. These technologies allow collection of information, analyzing and drawing meaningful insights from it in a more accurate, timely and reliable manner. IoT in this context refers to the use of IoT devices to convert data from surrounding elements a...

Nowadays it is critical to have the ability to quickly and reliably fetch huge amounts of heterogeneous data and apply Machine Learning (ML) models against it for better decision making. Successful processing of streams with data is crucial for real-time operations like extracting, filtering, transforming, aggregating with other data sources, persisting data to data warehouses, publishing to a different messaging topics or pipelines. With Machine Learning gaining high in popularity serious concerns are appearing a...

Machine Learning (ML) is the study and the usage of the mathematical algorithms which can improve their performance without the need for human interaction. These algorithms are considered as a subset of Artificial Intelligence (AI). Machine learning algorithms use past data as input and produce new predicted values as an output. Machine learning algorithms have been used in many areas for solving an innumerable number of tasks. However, the various tasks need applying of different machine learning algorithms for o...

The sustainable agriculture requires a series of complex, individual but interrelated and dependent on each other processes that need to be efficiently organized in stages to ensure good overall results. Therefore, the success of a given product is based on a triangle formed by the farmer, the technology and the concept of services and counseling. Services and counseling are based on collected data. Data generated from modern agricultural activities is extracted with the usage of various sensors embedded in agricu...

Internet of Things (IoT) has a different meaning to different people. The term has been known for a long time. The use of interconnected devices has become more and more necessary to solve established business problems. It turns out that data acquired from IoT sensors and controllers are valuable enough to have the power to change the overall business models and behaviour of entire industries in a given economy. Therefore, the future of IoT as a cutting-edge technology depends on the security capabilities that IoT...

With introduction of new and advanced technologies in beekeeping it is possible to design and use Internet of Things (IoT) sensor systems embedded in beehives. This provides the ability to collect heterogeneous data and to provide real-time remote monitoring. Complex prognostic models are applied after the data is manipulated and normalized. The obtained results are used to predict the processes occurring in beehives. For this purpose, the collected data must be divided into at least two parts for training and val...

With introduction of new and advanced technologies in beekeeping it is possible to design and use Internet of Things (IoT) sensor systems embedded in beehives. This provides the ability to collect heterogeneous data and to provide real-time remote monitoring. Complex prognostic models are applied after the data is manipulated and normalized. The obtained results are used to predict the processes occurring in beehives. For this purpose, the collected data must be divided into at least two parts for training and val...

The article reviews and analyzes the existing computer systems and platforms for the dynamic monitoring of bee hives, through which various states of bee colonies can be detected and analyzed. Contemporary solutions are based on the Internet of Things (IoT) concept and consist of a number of different sensors that collect several types of data about the internal condition of the hive. The article proposes a new model of IoT-based monitoring system, which consists of sensors being located inside and outside of bee ...