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Analysis of Ecological Environment Evaluation and Coupled and Coordinated Development of Smart Cities Based on Multisource Data
In order to further enhance the ecological environment construction of smart cities and promote its deep integration with advanced technologies, such as the new generation of artificial intelligence and big data, this study constructs a data fusion framework for the ecological environment of smart c...
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Published in: | Journal of sensors 2022-03, Vol.2022, p.1-9 |
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description | In order to further enhance the ecological environment construction of smart cities and promote its deep integration with advanced technologies, such as the new generation of artificial intelligence and big data, this study constructs a data fusion framework for the ecological environment of smart cities driven by multisource data and constructs an ecological environment evaluation index system of smart cities in Guangzhou from 2010 to 2018. The ecological environment status of smart cities in Guangzhou is analyzed by principal component analysis, and finally the, correlation influence degree of each principal component content on the ecological environment index of smart cities is analyzed. The results show that environmental excellence (K1), environmental restoration response (K2), and environmental pollution pressure (K3) are the main components of the ecological environment in Guangzhou smart city. The environmental excellence and environmental restoration response level are relatively high, and the environmental pressure system is relatively low, in which the greenland coverage rate increases from 41.3% to 44.0%, and the urban sewage treatment rate and the decontamination rate of urban refuse increase year by year, from 73.1% to 94.6% and from 72.1% to 99.9%, respectively. The results of principal component correlation analysis show that there are interactive influences among environmental excellence (K1), environmental restoration response (K2), and environmental pollution pressure (K3). The ecological environment index of smart cities increases with the improvement of environmental excellence and environmental restoration response capacity, but gradually decreases with the increase of environmental pollution pressure. Generally speaking, improving environmental excellence and environmental restoration response will be the key to improve the ecological environment construction capacity of smart cities in the future. |
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The ecological environment status of smart cities in Guangzhou is analyzed by principal component analysis, and finally the, correlation influence degree of each principal component content on the ecological environment index of smart cities is analyzed. The results show that environmental excellence (K1), environmental restoration response (K2), and environmental pollution pressure (K3) are the main components of the ecological environment in Guangzhou smart city. The environmental excellence and environmental restoration response level are relatively high, and the environmental pressure system is relatively low, in which the greenland coverage rate increases from 41.3% to 44.0%, and the urban sewage treatment rate and the decontamination rate of urban refuse increase year by year, from 73.1% to 94.6% and from 72.1% to 99.9%, respectively. The results of principal component correlation analysis show that there are interactive influences among environmental excellence (K1), environmental restoration response (K2), and environmental pollution pressure (K3). The ecological environment index of smart cities increases with the improvement of environmental excellence and environmental restoration response capacity, but gradually decreases with the increase of environmental pollution pressure. Generally speaking, improving environmental excellence and environmental restoration response will be the key to improve the ecological environment construction capacity of smart cities in the future.</description><identifier>ISSN: 1687-725X</identifier><identifier>EISSN: 1687-7268</identifier><identifier>DOI: 10.1155/2022/5959495</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Artificial intelligence ; Big Data ; Civilization ; Construction ; Correlation analysis ; Data integration ; Decontamination ; Digitization ; Ecological effects ; Industrial wastes ; Information technology ; Principal components analysis ; Restoration ; Smart cities ; Software ; Urbanization ; Variance analysis ; Water supply</subject><ispartof>Journal of sensors, 2022-03, Vol.2022, p.1-9</ispartof><rights>Copyright © 2022 Qianwei Ma and Yanxia Yang.</rights><rights>Copyright © 2022 Qianwei Ma and Yanxia Yang. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-9aae6d069202157c96097787496129e12211bc892f4a4f4416602f3e5040e8d13</citedby><cites>FETCH-LOGICAL-c337t-9aae6d069202157c96097787496129e12211bc892f4a4f4416602f3e5040e8d13</cites><orcidid>0000-0002-6710-1311</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2646636206/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2646636206?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><contributor>Zeng, Wen</contributor><contributor>Wen Zeng</contributor><creatorcontrib>Ma, Qianwei</creatorcontrib><creatorcontrib>Yang, Yanxia</creatorcontrib><title>Analysis of Ecological Environment Evaluation and Coupled and Coordinated Development of Smart Cities Based on Multisource Data</title><title>Journal of sensors</title><description>In order to further enhance the ecological environment construction of smart cities and promote its deep integration with advanced technologies, such as the new generation of artificial intelligence and big data, this study constructs a data fusion framework for the ecological environment of smart cities driven by multisource data and constructs an ecological environment evaluation index system of smart cities in Guangzhou from 2010 to 2018. The ecological environment status of smart cities in Guangzhou is analyzed by principal component analysis, and finally the, correlation influence degree of each principal component content on the ecological environment index of smart cities is analyzed. The results show that environmental excellence (K1), environmental restoration response (K2), and environmental pollution pressure (K3) are the main components of the ecological environment in Guangzhou smart city. The environmental excellence and environmental restoration response level are relatively high, and the environmental pressure system is relatively low, in which the greenland coverage rate increases from 41.3% to 44.0%, and the urban sewage treatment rate and the decontamination rate of urban refuse increase year by year, from 73.1% to 94.6% and from 72.1% to 99.9%, respectively. 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Generally speaking, improving environmental excellence and environmental restoration response will be the key to improve the ecological environment construction capacity of smart cities in the future.</description><subject>Artificial intelligence</subject><subject>Big Data</subject><subject>Civilization</subject><subject>Construction</subject><subject>Correlation analysis</subject><subject>Data integration</subject><subject>Decontamination</subject><subject>Digitization</subject><subject>Ecological effects</subject><subject>Industrial wastes</subject><subject>Information technology</subject><subject>Principal components analysis</subject><subject>Restoration</subject><subject>Smart cities</subject><subject>Software</subject><subject>Urbanization</subject><subject>Variance analysis</subject><subject>Water supply</subject><issn>1687-725X</issn><issn>1687-7268</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNp9kM1OwzAQhC0EEqVw4wEscYRQ24nt-Fja8COBOAASt8gkDrhy7WA7RT3x6ri04shpZ6VvRzsDwClGlxhTOiGIkAkVVBSC7oERZiXPOGHl_p-mr4fgKIQFQizneT4C31MrzTroAF0Hq8YZ964baWBlV9o7u1Q2wmolzSCjdhZK28KZG3qj2p12vtVWxrTP1UoZ1_-eJLOnpfQRznTUKsArGRKRDB4GE3Vwg28UnMsoj8FBJ01QJ7s5Bi_X1fPsNrt_vLmbTe-zJs95zISUirWIiRQRU94IhgTnJS8Ew0QoTAjGb00pSFfIoisKzBgiXa4oKpAqW5yPwdnWt_fuc1Ah1ov0RMoeasIKxnJGUiVjcLGlGu9C8Kqre69TjnWNUb2puN5UXO8qTvj5Fv_QtpVf-n_6BxAietc</recordid><startdate>20220324</startdate><enddate>20220324</enddate><creator>Ma, Qianwei</creator><creator>Yang, Yanxia</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SP</scope><scope>7U5</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>D1I</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KB.</scope><scope>L6V</scope><scope>L7M</scope><scope>M0N</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-6710-1311</orcidid></search><sort><creationdate>20220324</creationdate><title>Analysis of Ecological Environment Evaluation and Coupled and Coordinated Development of Smart Cities Based on Multisource Data</title><author>Ma, Qianwei ; 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subjects | Artificial intelligence Big Data Civilization Construction Correlation analysis Data integration Decontamination Digitization Ecological effects Industrial wastes Information technology Principal components analysis Restoration Smart cities Software Urbanization Variance analysis Water supply |
title | Analysis of Ecological Environment Evaluation and Coupled and Coordinated Development of Smart Cities Based on Multisource Data |
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