{"title":"无线通信的人工智能:昆虫的视角","authors":"Ramiro Samano Robles;Gowhar Javanmardi;Christoph Pilz;Przemyslaw Kwapisiewicz;Mateusz Rzymowski;Lukasz Kulas;Luca Davoli;Laura Belli;Gianluigi Ferrari;Bernd-Ludwig Wenning;Bugra Gonca;R. Venkatesha Prasad;Ashutosh Simha;Markku Kiviranta;Ilkka Moilanen;Sean Robinson;Gennaro Cirillo;Mujdat Soyturk;Yavuz Selim Bostanci;Leander B. Hörmann","doi":"10.1109/OJIES.2025.3560946","DOIUrl":null,"url":null,"abstract":"This article 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 cross-domain architecture design, which targets UCs assisted by reusable and/or interoperable technical Building Blocks (BBs). These BBs constitute the <italic>“bricks”</i> 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 collection, harmonization, refinement, classification, architecture alignment, and 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 of AI-enabled IoT systems. The article summarizes the SBBs related to wireless connectivity, including a general description, implementation issues, a comparison of results, adopted interfaces, and conclusions across domains.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"802-819"},"PeriodicalIF":4.3000,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10965931","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence for Wireless Communications: The InSecTT Perspective\",\"authors\":\"Ramiro Samano Robles;Gowhar Javanmardi;Christoph Pilz;Przemyslaw Kwapisiewicz;Mateusz Rzymowski;Lukasz Kulas;Luca Davoli;Laura Belli;Gianluigi Ferrari;Bernd-Ludwig Wenning;Bugra Gonca;R. Venkatesha Prasad;Ashutosh Simha;Markku Kiviranta;Ilkka Moilanen;Sean Robinson;Gennaro Cirillo;Mujdat Soyturk;Yavuz Selim Bostanci;Leander B. Hörmann\",\"doi\":\"10.1109/OJIES.2025.3560946\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article 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 cross-domain architecture design, which targets UCs assisted by reusable and/or interoperable technical Building Blocks (BBs). These BBs constitute the <italic>“bricks”</i> 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 collection, harmonization, refinement, classification, architecture alignment, and 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 of AI-enabled IoT systems. The article summarizes the SBBs related to wireless connectivity, including a general description, implementation issues, a comparison of results, adopted interfaces, and conclusions across domains.\",\"PeriodicalId\":52675,\"journal\":{\"name\":\"IEEE Open Journal of the Industrial Electronics Society\",\"volume\":\"6 \",\"pages\":\"802-819\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10965931\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Open Journal of the Industrial Electronics Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10965931/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of the Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10965931/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Artificial Intelligence for Wireless Communications: The InSecTT Perspective
This article 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 cross-domain architecture design, which targets UCs assisted by reusable and/or interoperable technical Building Blocks (BBs). These BBs constitute the “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 collection, harmonization, refinement, classification, architecture alignment, and 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 of AI-enabled IoT systems. The article summarizes the SBBs related to wireless connectivity, including a general description, implementation issues, a comparison of results, adopted interfaces, and conclusions across domains.
期刊介绍:
The IEEE Open Journal of the Industrial Electronics Society is dedicated to advancing information-intensive, knowledge-based automation, and digitalization, aiming to enhance various industrial and infrastructural ecosystems including energy, mobility, health, and home/building infrastructure. Encompassing a range of techniques leveraging data and information acquisition, analysis, manipulation, and distribution, the journal strives to achieve greater flexibility, efficiency, effectiveness, reliability, and security within digitalized and networked environments.
Our scope provides a platform for discourse and dissemination of the latest developments in numerous research and innovation areas. These include electrical components and systems, smart grids, industrial cyber-physical systems, motion control, robotics and mechatronics, sensors and actuators, factory and building communication and automation, industrial digitalization, flexible and reconfigurable manufacturing, assistant systems, industrial applications of artificial intelligence and data science, as well as the implementation of machine learning, artificial neural networks, and fuzzy logic. Additionally, we explore human factors in digitalized and networked ecosystems. Join us in exploring and shaping the future of industrial electronics and digitalization.