Guest Editor(s)
Dr. Christos L. Stergiou
Email: c.stergiou@uom.edu.gr
Affiliation: Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
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Research Interests: networks and security, systems programming, cloud computing, big data, wireless communication, artificial intelligence, internet applications, smart education, internet of things, 3D graphics design, big data analytics
Dr. Andreas P. Plageras
Email: a.plageras@uom.edu.gr
Affiliation: Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
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Research Interests: web design and development, application development, networks and security, systems programming, cloud and edge computing, big data technologies, big data analytics, artificial intelligence, automation, robotics, internet applications, smart education, 3D graphics design
Dr. Vasileios A. Memos
Email: vmemos@uom.edu.gr
Affiliation: Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
Homepage:
Research Interests: computer networks, wireless and mobile communications, multimedia transmission over 5G networks, cloud computing (CC), big data analytics (BDA), wireless sensor network (WSN), Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), cybersecurity, cryptography, privacy and security software testing
Prof. Dr. Konstantinos E. Psannis
Email: kpsannis@uom.edu.gr
Affiliation: Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
Homepage:
Research Interests: digital signals and systems, 6G-enabled-ubiquitous big data, AI-IoT, clouds and communications, digital media communications, media coding, media synchronization, transport over a variety of networks
Summary
Artificial Intelligence of Things (AIoT), cognitive cloud computing, and intelligent distributed architectures are reshaping modern computational ecosystems across multiple domains, including education, telecommunications, industrial automation, smart cities, and large‑scale data analytics. The integration of AI‑driven IoT infrastructures with cognitive cloud platforms enables autonomous decision‑making, real‑time analytics, adaptive resource management, and scalable web‑based applications capable of operating under uncertainty and dynamic environmental conditions. These emerging paradigms introduce new challenges related to intelligent automation, multimodal data processing, secure distributed learning, and the development of robust computational frameworks aligned with the principles of soft computing and intelligent systems.
This Special Issue aims to provide a high‑quality forum for researchers, practitioners, and industry experts to present cutting‑edge methodologies, theoretical advances, and real‑world applications in AIoT‑enabled cognitive cloud ecosystems. Submissions are encouraged in areas such as intelligent automation, distributed learning, edge–cloud collaboration, data‑driven modeling, optimization, and next‑generation web application development. Works that demonstrate interdisciplinary relevance, scalable architectures, optimization strategies, and robust intelligent systems—consistent with the Aim & Scope of Intelligent Automation & Soft Computing (IASC)—are particularly welcome.
Suggested themes include, but are not limited to:
AIoT‑Driven Intelligent Automation — Autonomous sensing, adaptive control, and intelligent decision‑making in distributed environments.
Cognitive Cloud Computing Architectures — Learning‑enabled cloud platforms, dynamic resource orchestration, and intelligent services.
Edge–Cloud Collaborative Intelligence — Real‑time analytics, federated learning, and distributed AI models across heterogeneous layers.
Data Analytics and Knowledge Extraction — Big data processing, multimodal analytics, predictive modeling, and intelligent decision support.
Web‑Enabled Intelligent Applications — AI‑driven web systems, smart services, scalable online platforms, and cloud‑native application development.
Secure and Trustworthy AIoT Systems — Privacy‑preserving computation, blockchain‑based trust, and resilient distributed infrastructures.
AIoT in Education and Smart Environments — Intelligent monitoring, adaptive learning systems, and context‑aware smart services.
Optimization and Soft Computing for Distributed Systems — Metaheuristics, fuzzy systems, evolutionary algorithms, and intelligent optimization.
Explainable and Human‑Centered AIoT — Interpretability, transparency, ethical AI, and user‑centric intelligent design.
6G‑Enabled IoT and Cognitive Communication Systems — Network slicing, ultra‑reliable low‑latency communication, and intelligent connectivity.
Keywords
AIoT, cognitive cloud computing, intelligent automation, edge intelligence, data analytics, web applications, soft computing, distributed learning, optimization, autonomous systems
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