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Subject
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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Beyond Smart and Connected Governments Sensors and the Internet of Things in the Public Sector

Springer, 2020.
Under the general editorship: J. R. Gil-Garcia, T. A. Pardo, M. Gasco-Hernandez

This book provides a comprehensive introduction to the study of sensors and the Internet of Things (IoT) from a government and public policy perspective. Since 2011, federal spending on IoT has been growing at a compound annual rate of ten percent. New technologies, such as sensors, and new kinds of data, such as big data, are creating new ways to systematically capture data and to use it to respond to complex problems. Some of these new technologies and applications have been identified and studied in recent literature in terms of their relevance to government. 

This volume adds to the literature by presenting sound theories and concepts for understanding the opportunities and challenges governments face when seeking to improve public services and government operations through the use of IoT. It also includes innovative methodologies for building understanding of the potential of a smart and connected government. In addition, the book offers relevant case studies and practical recommendations for the development, management, and evaluation of public policies and government programs.

Chapters
Use of the Internet of Things in Public Governance for Law Enforcement and Inspection: The Case of Russia
Knutov A., Styrin E. M., , in: Beyond Smart and Connected Governments Sensors and the Internet of Things in the Public Sector.: Springer, 2020. Ch. 7 P. 139–164.
The Internet of Things is being actively introduced in Russian public governance for inspection and oversight. In this chapter, based on an analysis of IoT policy, legal acts, secondary statistical data, and the authors’ own involvement in testing IoT technologies, we formulate cases and use them as a basis for an IoT classification oriented to ...
Added: May 5, 2020
Priority areas: state and public administration
Language: English
DOI
Text on another site
Keywords: innovationsmart cities Information technologyInternet of things (IoT)data analyticsInterconnectivityNetworks sensorsSmart Government
Beyond Smart and Connected Governments Sensors and the Internet of Things in the Public Sector
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