Artificial Intelligence (AI) represents one of the fastest growing areas of knowledge, sectors and fields of action globally. This growth has allowed to mark different positions, where the most favorable ones are oriented to its unquestionable contribution to facilitate decision making in various fields of society, as well as other sectors that mark a strong position for its use to be carried out in a regulated and measured way due to the scope and risks to which we are exposed. For this reason, rigorous methods are increasingly required for the design and development of AI-based computational models; methods that involve strict mechanisms for their validation, as well as the analysis of possible risks and scope that they may have on the field of application where they are being exposed. This type of aspects would definitely mark a valuable and relevant milestone to define several paths within which we can find two: 1) if it is definitely necessary to set limits on the use of AI by establishing increasingly sophisticated regulatory frameworks on various areas involving data protection and regulated use of the same, and 2) to remove all barriers so that it can be exploited openly in all its dimensions in any area of our society. Hence the importance of analysing the different risks and threats that AI may present within the particular context in which it is being applied.
Based on this panorama, this regular edition of the “International Journal Interactive Multimedia and Artificial Intelligence” presents a series of papers where proposals are oriented to different fields and sectors, which make use of diverse approaches, methods, models and AI-based systems that allow us to have a generalized idea of how these challenges are being addressed in some fields of our society. In particular, this regular issue collects research topics focusing on addressing the problems of evolving recommender systems, classification models, decision support systems, system modelling, data analytics, optimization algorithms, image retrieval, deep neural networks, social network analysis, and the relevance of the design of User Experience (UX) proposals.

With the rapid development of information and communication technologies, artificial intelligence and IoTs, more and more advanced technologies, such as machine learning, reinforcement learning, neural networks and fuzzy systems, have been introduced into industrial practices. The application of advanced technologies has greatly promoted the process of industrial revolution. However, there is big gap between controlled simulation and real evolving environment, which results in the unsatisfactory performance of the typical algorithms in practical environments. For example, in
Underwater IoTs, a dynamic and uncertain marine environment can cause equipment damage, resulting in huge financial losses. Therefore, improving the robustness and adaptability of algorithms and systems, and proposing new solutions in practical applications to meet the requirements of self-developing, self-organizing, and evolving systems is essential to promote intelligent industrial applications.
This Research Topic aims to collect researches focusing on addressing the problems of evolving system modelling, clustering, classification, prediction and control in non-stationary, unpredictable environments. The scope of this topic includes: (1) Robustness of environment modeling in evolutionary system, (2) Robustness of artificial intelligence algorithms, (3) Adaptability of neural networks and systems, (4) Prediction of intelligent algorithms in dynamic environments, (5) Improvement of robustness in deep learning algorithms, (6) Interpretability of predictive models in dynamic environments, (7) Application of AI technology in Industrial Internet of Things, (8) Uncertainty in Intelligent Transportation System, (9) The dynamic environment of Underwater Internet of Things, (10) Applications and migration of intelligent algorithms.

The International Journal of Interactive Multimedia and Artificial Intelligence – IJIMAI –provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances in Artificial Intelligence (AI) tools or tools that use AI with interactive multimedia techniques. The present regular issue includes 13 articles. The first block of articles deals with problems related to images as diverse as the artificial generation of images or the optimization of their storage and transmission through compression techniques. The applications are very diverse, including the identification of forgeries, tumors or even misplaced face masks. Another block contains only one paper on speech recognition targeted on specific users suffering from dysarthria. Other block of two articles focuses on the education field problems of automation of teachers’ certification processes or prediction of students’ academic failure. Last block of articles covers services and products, commerce, marketing and user experience issues, as well as the ethical implications of AI.

The international conference “Disruptive Technologies Tech Ethics and Artificial Intelligence” (DITTET) provides a forum to present and discuss the latest scientific and technical advances and their implications in the field of ethics. It also provides a forum for experts to present their latest research in disruptive technologies, promoting knowledge transfer. It provides a unique opportunity to bring together experts in different fields, academics, and professionals to exchange their experience in the development and deployment of disruptive technologies, artificial intelligence, and their ethical problems.

DITTET intends to bring together researchers and developers from industry, humanities, and academia to report on the latest scientific advances and the application of artificial intelligence, as well as its ethical implications in fields as diverse as climate change, politics, economy or security in today’s world.

This Special Issue contains extended versions of selected works presented at the 1st International Conference on Disruptive Technologies, Tech Ethics and Artificial Intelligence (DiTTEt 2021), held in Salamanca (Spain) in September 2021.

As the Internet of Things (IoT) further develops and expands to the Internet of Everything (IoE), high-speed multimedia streaming data processing, analysis, and shorter response times are increasingly becoming the demands of today. Driven by the Internet of Things (IoT), a new computing paradigm, Edge computing, is currently developing rapidly. Compared with traditional centralized generalpurpose computing, Edge computing is a distributed architecture. The operations of applications, data and services are moved from the central node of the network to the edge nodes on the network logic for processing. Under this structure, the analysis of data and the generation of knowledge are closer to the source of the data, so it is more suitable for processing. However, with the rapid development of 5G, IoT and other services and scenarios, there are more and more intelligent terminal devices. Multimedia streaming processing in IoT becomes a very prominent problem. To overcome this problem, the adoption of intelligent Edge or Artificial Intelligence (AI) powered Edge computing (Edge-AI) can achieve the goals of lower cost, higher security, lower latency, and ease of management.
Recently, many network modeling methods, computing algorithms, and signal processing technologies have been successfully developed and applied to multimedia streaming processing in IoT with Edge Intelligence. A total of 13 papers are presented in this special issue for the purpose of collecting the latest developments and results on this research topic. We divide them into three categories: production and life applications, security, and text and image processing.

The International Journal of Interactive Multimedia and Artificial Intelligence – IJIMAI (ISSN 1989-1660) provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances in Artificial Intelligence (AI) tools or tools that use AI with interactive multimedia techniques. The present volume (June 2022), consists of 20 articles of diverse applications of great impact in several fields. The issue consistently showcases the utilization of AI techniques or mathematical models with an artificial intelligence base, as a standard element. Different manuscripts on usability and satisfaction, machine learning models, genetic algorithms, computer entertainment technologies, oral pathologies, optimistic motion planning, data analysis for decision making, etc. can be found in this volume.

Machine learning (ML) is generating new opportunities for innovative research in areas apparently unrelated such as, economics, business or/and finance. Specifically, it has also been widely used in applications related to the economic and financial analysis, such as economic recessions prediction, labor market trends, risk management, prices analysis among others. However, it is important to note the differences between classical statistics/econometrics and machine learning. On the one hand, econometrics set out to build models designed to describe economic problems, while machine learning uses algorithms, generally for prediction, classification, and also, can manage a large amount of structured and unstructured data and make fast decisions or forecasts. As S. Athey points out, perhaps “a key advantage of ML is that it frames empirical analysis in terms of algorithms that estimate and compare many alternative models. This approach contrasts with econometrics, where (in principle, though rarely in reality) the researcher picks a model based on principles and estimates it once”. This Special Issue presents nine contributions that illustrate both approaches in the domain of economics, finance and business.

The International Journal of Interactive Multimedia and Artificial Intelligence - IJIMAI - provides a space in which scientists and professionals can report about new advances in Artificial Intelligence (AI). On this occasion, for the last edition of the year, I am pleased to present a regular issue including different investigations covering aspects and problems in AI and its use in various fields such as medicine, education, image analysis, protection of data, among others.

Research on the relationship between computing and the meaning of human life flourishes proportionally to the increasing digitalization of our world. More and more, reflections on ethics and politics, spiritual values and religious experiences, beliefs, and practices make use of digital media in order to spread their content or express themselves. If we still consider that there is truth in the well-known dictum that “the medium is the message”, then it is worth asking how the content of these reflections and practices are changing today. Every change is the introduction of something new, and this novelty can be interpreted either as the improvement or the worsening of the current situation. Generally speaking, research on either the positive or negative interactions between the advances in AI and the dimension of spirituality and analogue thinking are based on at least three approaches. The first produces analogies between concepts from human studies and concepts from computer science; for instance, speaking of “modeling” for concepts in human sciences, or considering the universe to be intelligently organized in an algorithmic order. The second approach is the application of research on AI and computer science to develop new insights on the extents, limits, and perfectibility of spiritual topics, discussions, or even practices. Finally, the third approach applies sociological, philosophical, aesthetic, or even theological concepts to assess the changes that digitalization introduces in spiritual practices, beliefs, and cultures. This special issue analyzes the current state of the art, and it addresses all three models of the research. By doing so, the issue will place the general question of the distinction between human and machine into sharper relief.

In today’s world, we have witnessed an onset of multimedia content being uploaded/downloaded and shared through a multitude of platforms both online and offline. In support of this trend, multimedia processing and analyzing has become very popular in all kinds of information extraction and attracts research interest from both academia and industry. This is to be expected as the multimedia digital world is worth trillions of dollars worldwide. However, multimedia information is hard to encode, interpret and recognize because it is combined with many complex components. Recently, there are many research areas related to the overall notion of intelligent multimedia processing. Therefore, the collected papers in this special issue provide a systematic overview and state-of-the-art research in the field of intelligent multimedia processing and analyzing system and outline new developments in fundamental, theorems, approaches, methodologies, software systems, recommendations, and real-world applications in this area.