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			<journal-title xml:lang="ru">СТРОИТЕЛЬНЫЕ И ДОРОЖНЫЕ МАШИНЫ</journal-title><trans-title-group xml:lang="en"><trans-title>STROITEL'NYE I DOROZHNYE MASHINY</trans-title></trans-title-group>
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			<article-id pub-id-type="publisher-id">73</article-id>
			<article-categories><subj-group subj-group-type="heading" xml:lang="en"><subject>MACHINES AND MECHANISMS</subject></subj-group><subj-group subj-group-type="heading" xml:lang="ru"><subject>МАШИНЫ И МЕХАНИЗМЫ</subject></subj-group></article-categories>
			<title-group><article-title xml:lang="ru">Интеграция искусственного интеллекта и киберфизических систем в адаптивной автоматизации строительных процессов: эмпирический анализ эффективности</article-title><trans-title-group xml:lang="en"><trans-title>Integration of artificial intelligence and cyber-physical systems in adaptive automation of construction processes: an empirical analysis of efficiency</trans-title></trans-title-group></title-group>
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						<name name-style="western" specific-use="primary" xml:lang="ru">
							<surname>Захаров</surname>
							<given-names>Павел Валентинович</given-names>
						</name>
						<name name-style="western" xml:lang="en">
							<surname>Zakharov</surname>
							<given-names>Pavel V.</given-names>
						</name>
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					<email>zakharovpv@student.bmstu.ru</email>
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						<name name-style="western" specific-use="primary" xml:lang="ru">
							<surname>Басараб</surname>
							<given-names>Михаил Алексеевич</given-names>
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						<name name-style="western" xml:lang="en">
							<surname>Basarab</surname>
							<given-names>Mikhail A.</given-names>
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					<email>basarab@bmstu.ru</email>
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				<aff xml:lang="ru"><institution content-type="orgname">Московский государственный технический университет им. Н.Э. Баумана</institution></aff>
				<aff xml:lang="en"><institution content-type="orgname">Bauman Moscow State Technical University</institution></aff>
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			<pub-date date-type="collection"><year>2025</year></pub-date><pub-date date-type="pub" publication-format="epub"><day>30</day><month>07</month><year>2025</year></pub-date>
			<volume seq="1">69</volume>
			<issue>7</issue>
				<issue-id>9</issue-id><issue-title xml:lang="ru">Строительные и дорожные машины </issue-title><issue-title xml:lang="en">Stroitel'nye i dorozhnye mashiny</issue-title><fpage>59</fpage>
				<lpage>69</lpage>
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				<copyright-statement xml:lang="en">© 2025 STROITEL'NYE I DOROZHNYE MASHINY. All rights reserved.</copyright-statement>
				<copyright-year>2025</copyright-year>
				<copyright-holder xml:lang="ru">СТРОИТЕЛЬНЫЕ И ДОРОЖНЫЕ МАШИНЫ</copyright-holder>
				<copyright-holder xml:lang="en">STROITEL'NYE I DOROZHNYE MASHINY</copyright-holder>
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			<abstract xml:lang="ru"><p>Строительная индустрия сталкивается с критическими вызовами в области производительности, безопасности и устойчивого развития, требующими внедрения передовых технологических решений. Данное исследование представляет эмпирический анализ интеграции искусственного интеллекта и киберфизических систем в строительных процессах на основе анализа 92% строительных компаний, использующих или планирующих использовать технологии ИИ. Методологический аппарат включает анализ данных из глобальных отраслевых исследований McKinsey, Boston Consulting Group и Motive Safety Reports, охватывающих период 2022-2024 годов. Результаты демонстрируют потенциал повышения производительности строительства до 20% при использовании ИИ-технологий, автоматизации до 30% строительных работ к 2025 году и снижения количества несчастных случаев на 72% при внедрении систем компьютерного зрения. Анализ рынка показывает рост от 3,99 млрд долларов в 2024 году до 11,85 млрд долларов к 2029 году с темпом роста 24,31% в год. Исследование выявляет, что 61% респондентов отмечают существенные улучшения в обнаружении ошибок при использовании BIM-технологий, а 55% наблюдают значительное сокращение времени принятия решений. Практическая значимость работы заключается в предоставлении доказательной базы для обоснования инвестиций в интеллектуальные строительные технологии и определении приоритетных направлений цифровой трансформации отрасли.</p></abstract><trans-abstract xml:lang="en"><p>The construction industry is facing critical challenges in the areas of productivity, safety and sustainability, requiring the introduction of advanced technological solutions. This study provides an empirical analysis of the integration of artificial intelligence and cyber-physical systems in construction processes based on an analysis of 92% of construction companies using or planning to use AI technologies. The methodological framework includes the analysis of data from global industry research by McKinsey, Boston Consulting Group and Motive Safety Reports covering the period 2022-2024. The results demonstrate the potential to increase construction productivity by up to 20% using AI technologies, automate up to 30% of construction work by 2025, and reduce accidents by 72% with the introduction of computer vision systems. Market analysis shows growth from $3.99 billion in 2024 to $11.85 billion by 2029, with a growth rate of 24.31% per year. The study reveals that 61% of respondents note significant improvements in error detection when using BIM technologies, and 55% observe a significant reduction in decision-making time. The practical significance of the work lies in providing an evidence base to justify investments in intelligent construction technologies and identify priority areas for the digital transformation of the industry.</p></trans-abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>artificial intelligence</kwd><kwd>cyber-physical systems</kwd><kwd>construction automation</kwd><kwd>computer vision</kwd><kwd>predictive analytics</kwd><kwd>BIM</kwd><kwd>construction safety</kwd></kwd-group><kwd-group xml:lang="ru"><title>Ключевые слова</title><kwd>искусственный интеллект</kwd><kwd>киберфизические системы</kwd><kwd>строительная автоматизация</kwd><kwd>компьютерное зрение</kwd><kwd>предиктивная аналитика</kwd><kwd>BIM</kwd><kwd>безопасность строительства</kwd></kwd-group><funding-group>
				<funding-statement xml:lang="ru">Исследование выполнено без внешнего финансирования.</funding-statement>
				<funding-statement xml:lang="en">The study was conducted without external funding.</funding-statement>
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