Digital twins

Building smart factories in the university lab

August 5, 2026 by Ashish Jagani, Nikunj Rachchh

Smart factories are no longer the exclusive domain of multinational manufacturing corporations with extensive infrastructure and costly automation systems. Engineering students can now design, test, validate, and optimize entire smart factory ecosystems within their laboratories using advanced simulation platforms such as FlexSim and AnyLogic. Free trial versions, academic … [Read more...] about Building smart factories in the university lab

Digital twin of wireless channels for the intelligent transportation system

September 19, 2025 by Meiwen Zhang, Ke Guan, Danping He, Andrej Hrovat, Tomaž Javornik,

Abstract: With the gradual advancement of the intelligent transportation system (ITS), the digital twin of wireless channels (DTWC), as one of the critical technologies for future ITS network evolution, has received widespread attention. This article presents the architecture, characteristics, and critical technologies of DTWC systems for ITSs. With the rapid development of … [Read more...] about Digital twin of wireless channels for the intelligent transportation system

Privacy-preserving distributed learning: Techniques, applications, and future challenges

The rapid increase in data generated by connected devices has created a pressing need for privacy-preserving techniques in distributed learning. This article examines methods that enable collaborative machine learning (ML) while maintaining data security and user privacy. Key approaches such as federated learning (FL), differential privacy (DP), secure multiparty computation (SMPC), and homomorphic encryption (HE) are analyzed for their unique capabilities and various applications. FL facilitates model training across decentralized data sources, ensuring data remain local, while DP mitigates privacy risks by adding controlled noise. SMPC and HE support secure computations on encrypted data, maintaining confidentiality during processing. Despite their effectiveness, these techniques face challenges related to computational complexity, scalability, and regulatory compliance. The article reviews current advancements, practical implementations, and future directions, emphasizing the need for optimized, accessible solutions to enhance data security in distributed systems.

Digital twins

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