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News
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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?

Social Media Monitoring Practices by Smart Cities: Benefits and Risks

Ch. 4. P. 73–92.
Telitsyna A., Rudchenko A., Usanova K., Kornaukhov I.

This chapter highlights promising digital solutions for smart cities to improve urban feedback loops. The chapter discusses using media monitoring, artificial intelligence techniques, urban apps, and community structures to meet the challenge of identifying and evaluating problems faced by city authorities and public utilities. The chapter utilizes expert interviews and case studies to demonstrate the systems approach, including the development of urban apps, bots, communities, and media monitoring systems. It highlights the pros and cons of various options and emphasizes media monitoring as a potential alternative. The major objectives include detecting and assessing urban issues using objective data, improving response times, reducing crime, evaluating problem-solving dynamics, reviewing city PR, and assessing municipality performance. The chapter discusses two methods for media monitoring: one based on user reactions (likes, reposts, comments) and another based on message count. 74The next section covers media monitoring system implementation, including language model creation, AI-based sentiment analysis, and spam prevention measures. This highlights the importance of AI technologies like computer vision and text recognition in media analysis. The chapter covers data analytic approaches for media monitoring, such as seasonal smoothing, alert systems, and strategy comparisons. Additionally, it addresses the difficulties and constraints of conveying a message’s tone.

Language: English
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Keywords: smart citiessocial media monitoringPublic acceptance
Publication based on the results of:
Self-organization of citizens and the public administration system: a theory of mutual influence, the experience of Russia and other non-western countries and ways of improving the effectiveness of productive interaction (2025)

In book

The Role of Smart Technology and Industry 4.0 in Shaping Smart Cities
The Role of Smart Technology and Industry 4.0 in Shaping Smart Cities
CRC Press, 2026.
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