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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...

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...

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...