{"id":18293,"date":"2025-02-14T17:16:55","date_gmt":"2025-02-14T17:16:55","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=18293"},"modified":"2025-02-14T17:16:56","modified_gmt":"2025-02-14T17:16:56","slug":"new-ai-framework-for-more-sustainable-urban-planning","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/new-ai-framework-for-more-sustainable-urban-planning\/","title":{"rendered":"New AI Framework for More Sustainable Urban Planning"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-uagb-blockquote uagb-block-e7eb3fc3 uagb-blockquote__skin-border uagb-blockquote__stack-img-none\"><blockquote class=\"uagb-blockquote\"><div class=\"uagb-blockquote__content\">Researchers from Peking University and the University of Southern Denmark have developed a cutting-edge AI framework capable of identifying building materials with high precision. This breakthrough promises to significantly enhance sustainable urban planning and carbon reduction efforts worldwide.<\/div><footer><div class=\"uagb-blockquote__author-wrap uagb-blockquote__author-at-left\"><\/div><\/footer><\/blockquote><\/div>\n\n\n\n<div class=\"wp-block-group is-content-justification-space-between is-nowrap is-layout-flex wp-container-core-group-is-layout-b0ffac9c wp-block-group-is-layout-flex\"><div style=\"font-size:16px\" class=\"has-text-align-left wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">The University Network<\/p><\/div><\/div>\n\n\n<div class=\"wp-block-uagb-social-share uagb-social-share__outer-wrap uagb-social-share__layout-horizontal uagb-block-ee584a31\">\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-ec619ce7\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.facebook.com\/sharer.php?u=\" tabindex=\"0\" role=\"button\" aria-label=\"facebook\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M504 256C504 119 393 8 256 8S8 119 8 256c0 123.8 90.69 226.4 209.3 245V327.7h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.28c-30.8 0-40.41 19.12-40.41 38.73V256h68.78l-11 71.69h-57.78V501C413.3 482.4 504 379.8 504 256z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-32d99934\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/twitter.com\/share?url=\" tabindex=\"0\" role=\"button\" aria-label=\"twitter\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-1d136f14\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.linkedin.com\/shareArticle?url=\" tabindex=\"0\" role=\"button\" aria-label=\"linkedin\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><path d=\"M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n<\/div>\n<\/div>\n\n\n\n<p class=\"wp-block-paragraph\">A new era in sustainable urban planning is on the horizon, thanks to a recent study that leverages artificial intelligence and remote sensing technologies to identify building materials with unprecedented accuracy. <\/p>\n<\/div><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">The research, a collaboration between Peking University and the University of Southern Denmark, promises to revolutionize how cities plan and retrofit buildings for better energy efficiency and reduced carbon emissions.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A Transformative Framework<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S266649842500016X\" target=\"_blank\" rel=\"noopener\" title=\"\">Published<\/a> recently in Environmental Science and Ecotechnology, the research introduces an advanced framework that marries deep learning techniques with remote sensing. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This approach enables the creation of high-resolution material intensity databases, crucial for sustainable city planning. The AI-powered system meticulously classifies materials used in buildings, paving the way for significant reductions in embodied carbon and energy use while promoting urban circularity.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Conventional methods for assessing building materials often falter due to geographic limitations, scalability issues and lack of precision. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In contrast, this new framework offers a scalable, adaptable solution, poised to overcome these long-standing challenges and deliver actionable insights on a large scale.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A Collaborative Effort<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The study utilizes an innovative blend of Google Street View imagery, satellite data and geospatial information from OpenStreetMap to accurately classify rooftop and fa\u00e7ade materials. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">By training Convolutional Neural Networks (CNNs) with extensive datasets from Odense, Denmark, the researchers developed models capable of delivering precise material identification. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The framework demonstrated its versatility and accuracy when applied to other major Danish cities like Copenhagen, Aarhus and Aalborg.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Enhanced Model Transparency<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">One of the key innovations of the study is the application of Gradient-weighted Class Activation Mapping (Grad-CAM). This technique provides a visual representation of which parts of an image most influence the AI&#8217;s material classification decisions, enhancing model transparency and reliability. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Additionally, the researchers developed material intensity coefficients to quantify the environmental impact of different materials, further enabling refined sustainability assessments.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Broader Implications<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Gang Liu, the project&#8217;s principal investigator and chair professor of industrial ecology at Peking University and adjunct professor at  the University of Southern Denmark, emphasized the broader impact of this technological advancement<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">&#8220;Our study demonstrates how deep learning and remote sensing can fundamentally change the way we analyze and manage urban building materials,&#8221; he said in a <a href=\"https:\/\/www.eurekalert.org\/news-releases\/1073623\" target=\"_blank\" rel=\"noopener\" title=\"\">news release<\/a>. &#8220;With precise material intensity data, we can drive more sustainable urban planning and targeted retrofitting, contributing directly to global carbon reduction efforts.&#8221;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This framework not only bolsters academic research but also equips urban planners with critical data for implementing energy efficiency strategies, carbon reduction policies and circular economy initiatives. Its scalability and adaptability mean that it can be applied to diverse urban environments worldwide, making it a cornerstone for modern, sustainable city planning.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A new era in sustainable urban planning is on the horizon, thanks to a recent study that leverages artificial intelligence and remote sensing technologies to identify building materials with unprecedented accuracy. The research, a collaboration between Peking University and the University of Southern Denmark, promises to revolutionize how cities plan and retrofit buildings for better [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-no-separators","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8],"tags":[],"class_list":["post-18293","post","type-post","status-publish","format-standard","hentry","category-ai"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.8 - aioseo.com -->\n\t<meta name=\"description\" content=\"Researchers develop AI-based framework to identify building materials with high precision, enhancing sustainable urban planning and carbon reduction efforts.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"The University Network\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/www.tun.com\/home\/new-ai-framework-for-more-sustainable-urban-planning\/\" \/>\n\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 4.9.8\" \/>\n\t\t<meta property=\"og:locale\" content=\"en_US\" \/>\n\t\t<meta property=\"og:site_name\" content=\"TUN - 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The research, a collaboration between Peking University and the University of Southern Denmark, promises to revolutionize how cities plan and retrofit buildings for better&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/18293","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/comments?post=18293"}],"version-history":[{"count":10,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/18293\/revisions"}],"predecessor-version":[{"id":18353,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/18293\/revisions\/18353"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=18293"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=18293"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=18293"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}