Artificial Intelligence for Wireless Communications: The InSecTT perspective


Robles R. S., Javanmardi G., Pilz C., Kwapisiewicz P., Rzymowski M., Kulas L., ...Daha Fazla

IEEE Open Journal of the Industrial Electronics Society, cilt.6, ss.802-819, 2025 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 6
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1109/ojies.2025.3560946
  • Dergi Adı: IEEE Open Journal of the Industrial Electronics Society
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
  • Sayfa Sayıları: ss.802-819
  • Anahtar Kelimeler: Artificial intelligence (AI), edge computing, Internet-of-Things (IoT), reference architecture (RA), wireless
  • Marmara Üniversitesi Adresli: Evet

Özet

This paper presents an overview of how Artificial Intelligence (AI) and edge technology have been used to improve wireless connectivity in multiple industrial Use Cases (UCs) of the EU project "Intelligent Secure Trustable Things"(InSecTT). We present a brief introduction of the InSecTT framework for crossdomain architecture design, which targets UCs assisted by reusable and-or interoperable technical Building Blocks (BBs). These BBs constitute the construction bricks containing AI and supporting components that were used to build different UCs. The framework consists of multiple stages based on the processing of UC-BB requirements (RQs). These stages include: i) collection, ii) harmonization, iii) refinement, iv) classification, v) architecture alignment, and vi) functionality modeling of RQs. The most relevant results of these stages are discussed here, with emphasis on the need for a refined granularity of technical components with common functionalities named sub-building blocks (SBBs), where collaboration and cross-domain reusability were optimized. The design process shed light on how AI and SBBs were implemented across different layers and entities of our reference architecture for the Internet-of-Things (IoT), including the interfaces used for information exchange. This detailed interface analysis is expected to reveal issues such as bottlenecks, constraints, vulnerabilities, scalability problems, security threats, etc. This will, in turn, contribute to identifying design gaps in AI-enabled IoT systems. The paper summarizes the SBBs related to wireless connectivity, including a general description, implementation issues, comparison of results, adopted interfaces, and conclusions across domains.