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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd">
<article article-type="research-article" dtd-version="1.2" xml:lang="ru" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><front><journal-meta><journal-id journal-id-type="issn">2518-1092</journal-id><journal-title-group><journal-title>Research result. Information technologies</journal-title></journal-title-group><issn pub-type="epub">2518-1092</issn></journal-meta><article-meta><article-id pub-id-type="doi">10.18413/2518-1092-2021-6-4-0-7</article-id><article-id pub-id-type="publisher-id">2635</article-id><article-categories><subj-group subj-group-type="heading"><subject>ARTIFICIAL INTELLIGENCE AND DECISION MAKING</subject></subj-group></article-categories><title-group><article-title>&lt;strong&gt;ON THE POSSIBILITIES OF APPLYING MACHINE LEARNING&amp;nbsp;IN LIGHTING CONTROL SYSTEMS&lt;/strong&gt;
&lt;div&gt;&amp;nbsp;&lt;/div&gt;</article-title><trans-title-group xml:lang="en"><trans-title>&lt;strong&gt;ON THE POSSIBILITIES OF APPLYING MACHINE LEARNING&amp;nbsp;IN LIGHTING CONTROL SYSTEMS&lt;/strong&gt;
&lt;div&gt;&amp;nbsp;&lt;/div&gt;</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Roslyakova</surname><given-names>Svetlana Vitalievna</given-names></name><name xml:lang="en"><surname>Roslyakova</surname><given-names>Svetlana Vitalievna</given-names></name></name-alternatives><email>svetlana.roslyakova@itmo.ru</email></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Bragina</surname><given-names>Tatiana Vladimirovna</given-names></name><name xml:lang="en"><surname>Bragina</surname><given-names>Tatiana Vladimirovna</given-names></name></name-alternatives><email>bragina.arch@yandex.ru</email></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Zemlyanova</surname><given-names>Ekaterina Igorevna</given-names></name><name xml:lang="en"><surname>Zemlyanova</surname><given-names>Ekaterina Igorevna</given-names></name></name-alternatives><email>katya-zemlyanova95@yandex.ru</email></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Korotkova</surname><given-names>Daria Valerievna</given-names></name><name xml:lang="en"><surname>Korotkova</surname><given-names>Daria Valerievna</given-names></name></name-alternatives><email>dvkorotkova@itmo.ru</email></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Merkulova</surname><given-names>Polina Alekseevna</given-names></name><name xml:lang="en"><surname>Merkulova</surname><given-names>Polina Alekseevna</given-names></name></name-alternatives><email>merkulowapolina@gmail.com</email></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Laushkina</surname><given-names>Аnastasia Alexandrovna</given-names></name><name xml:lang="en"><surname>Laushkina</surname><given-names>Аnastasia Alexandrovna</given-names></name></name-alternatives><email>nastasjalausckina@mail.ru</email></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Filippov</surname><given-names>Ilya Mikhailovich</given-names></name><name xml:lang="en"><surname>Filippov</surname><given-names>Ilya Mikhailovich</given-names></name></name-alternatives><email>imphilippov@itmo.ru</email></contrib></contrib-group><pub-date pub-type="epub"><year>2021</year></pub-date><volume>6</volume><issue>4</issue><fpage>0</fpage><lpage>0</lpage><self-uri content-type="pdf" xlink:href="/media/information/2021/4/IT-7_Nw49Ddr.pdf" /><abstract xml:lang="ru"><p>Lighting control systems have been developing and improving in the last 10-20 years. The smart lighting market will only grow shortly. Traditional control algorithms (schedule, astronomical schedule, motion and presence sensors) cannot provide either the required levels of visual comfort or the optimal energy consumption of the lighting system. In addition, it should be noted that there is a tendency for modern users to increase the requirements for personalizing lighting conditions and flexibility in changing them. There are several directions for developing lighting control systems: biodynamic lighting, reducing energy consumption, focusing on visual comfort. The article proposes to consider machine learning as a promising and new approach in lighting control systems. The existing lighting control systems and scientific research in this area are analyzed in terms of their orientation. Machine learning has several advantages and disadvantages. Its initial implementation is quite complicated, but it is possible to simplify the setup and operation of lighting control systems significantly with its further use.</p></abstract><trans-abstract xml:lang="en"><p>Lighting control systems have been developing and improving in the last 10-20 years. The smart lighting market will only grow shortly. Traditional control algorithms (schedule, astronomical schedule, motion and presence sensors) cannot provide either the required levels of visual comfort or the optimal energy consumption of the lighting system. In addition, it should be noted that there is a tendency for modern users to increase the requirements for personalizing lighting conditions and flexibility in changing them. There are several directions for developing lighting control systems: biodynamic lighting, reducing energy consumption, focusing on visual comfort. The article proposes to consider machine learning as a promising and new approach in lighting control systems. The existing lighting control systems and scientific research in this area are analyzed in terms of their orientation. Machine learning has several advantages and disadvantages. Its initial implementation is quite complicated, but it is possible to simplify the setup and operation of lighting control systems significantly with its further use.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>machine learning</kwd><kwd>adaptive lighting</kwd><kwd>control systems</kwd><kwd>model training</kwd><kwd>personalization</kwd><kwd>energy efficiency</kwd><kwd>visual comfort</kwd><kwd>artificial lighting</kwd></kwd-group><kwd-group xml:lang="en"><kwd>machine learning</kwd><kwd>adaptive lighting</kwd><kwd>control systems</kwd><kwd>model training</kwd><kwd>personalization</kwd><kwd>energy efficiency</kwd><kwd>visual comfort</kwd><kwd>artificial lighting</kwd></kwd-group></article-meta></front><back><ack><p>Это исследование было реализовано с помощью международной образовательной программы &amp;ldquo;Световой дизайн&amp;rdquo; и Национального центра когнитивных разработок Университета ИТМО. Авторы хотели бы выразить особую благодарность руководителю лаборатории &amp;ldquo;Когнитивная невербалика&amp;rdquo; Олегу Олеговичу Басову, доктору технических наук, профессору факультета цифровых трансформаций Университета ИТМО.</p></ack></back></article>