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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Enabling Industrial Internet of Things With Wi-Fi 6: An Automated Factory Case Study

IEEE Transactions on Industrial Informatics. 2024. Vol. 20. No. 11. P. 13090–13100.
Anton Karamyshev, Liubogoshchev M., Andrey Lyakhov, Evgeny Khorov
In press

Industrial Internet of Things applications require low and deterministic delays, which is a challenging target for emerging wireless communication technologies. While the upcoming Wi-Fi 7 and Wi-Fi 8, tailored for real-time and reliable communications, are under development, this article focuses on Wi-Fi 6 and explores its capabilities to support industrial applications. This article summarizes key lessons learned during an industrial project on factory automation with Wi-Fi 6, describes and advocates a solution that satisfies quality of service requirements in industrial scenarios. To generalize the designed scheme, this article proposes a framework that maximizes the capacity of the system under reliability and latency constraints. Through extensive simulations, this article shows that the proposed scheme more than doubles the network capacity compared with the default Wi-Fi 6 implementation in terms of the number of stations served with low and deterministic packet delivery delays.

Research target: Computer Science Electronics and Electrical Engineering
Language: English
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Keywords: IEEE 802.11axQuality of Service (QoS)Industrial Internet of Things (IIoT)Wi-Fi 6 industrial applications
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