{"id":10560,"date":"2025-01-26T10:52:12","date_gmt":"2025-01-26T10:52:12","guid":{"rendered":"https:\/\/k3ylabs.com\/?p=10560"},"modified":"2025-07-02T10:34:56","modified_gmt":"2025-07-02T10:34:56","slug":"refine","status":"publish","type":"post","link":"https:\/\/k3ylabs.com\/el\/research-development\/projects\/refine\/","title":{"rendered":"REFINE"},"content":{"rendered":"
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Project Objective<\/h3>\n
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Air pollution is a significant global concern causing an estimated 4.2 million deaths annually due to diseases related to poor air quality. Climate change is exacerbating air quality issues and posing unprecedented challenges to the existing air quality monitoring systems, which mainly utilize sparse and expensive terrestrial stations and satellites, leading to limited accuracy and flexibility. To address these challenges, REFINE aims to form an international, multidisciplinary, and cross-sectoral consortium with world-leading researchers to create a novel real-time fine-grained air quality monitoring system empowered by advanced technologies in Unmanned Aerial Vehicles (UAVs), Artificial Intelligence (AI), and Wireless Networking.<\/p>\n

Specifically, REFINE will pioneer research and innovations (R&I) on ground-breaking technologies including: 1) a robust and scalable system architecture for aerial-terrestrial air quality monitoring; 2) intelligent and efficient multi-UAV cooperation strategies for dynamic and flexible area coverage; 3) ultra-resilient and secure aerial-terrestrial networking schemes for reliable and efficient data transmission; 4) lightweight and robust AI methods for accurate and real-time air quality analysis. REFINE will establish a long-term cross-disciplinary and cross-sectoral knowledge-sharing platform with competent and complementary expertise in Computer Science, Environmental Science, and Communication Engineering. The researchers involved will be trained through substantial R&I actions and well-planned networking activities at both European and global levels to enrich their skills and enhance their career perspectives.<\/p>\n

REFINE will significantly contribute to achieving the EU\u2019s zero-pollution ambition and enhancing European competitiveness, through transforming the current air quality monitoring systems into a new generation, which is able to provide real-time intelligent monitoring of vast rural areas with higher precision and efficiency.<\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Real-time Fine-grained Air Quality Monitoring with Intelligent and Robust Multi-UAV Networks<\/p>","protected":false},"author":4,"featured_media":10563,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-10560","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-projects","entry"],"yoast_head":"\nREFINE - k3y<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/k3ylabs.com\/el\/research-development\/projects\/refine\/\" \/>\n<meta property=\"og:locale\" content=\"el_GR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"REFINE - k3y\" \/>\n<meta property=\"og:description\" content=\"Real-time Fine-grained Air Quality Monitoring with Intelligent and Robust Multi-UAV Networks\" \/>\n<meta property=\"og:url\" content=\"https:\/\/k3ylabs.com\/el\/research-development\/projects\/refine\/\" \/>\n<meta property=\"og:site_name\" content=\"k3y\" \/>\n<meta property=\"article:published_time\" content=\"2025-01-26T10:52:12+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-07-02T10:34:56+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/k3ylabs.com\/wp-content\/uploads\/2025\/01\/REFINE_logo.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"k3y news\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u03a3\u03c5\u03bd\u03c4\u03ac\u03c7\u03b8\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc\" \/>\n\t<meta name=\"twitter:data1\" content=\"k3y news\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u0395\u03ba\u03c4\u03b9\u03bc\u03ce\u03bc\u03b5\u03bd\u03bf\u03c2 \u03c7\u03c1\u03cc\u03bd\u03bf\u03c2 \u03b1\u03bd\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7\u03c2\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 \u03bb\u03b5\u03c0\u03c4\u03ac\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/k3ylabs.com\\\/research-development\\\/projects\\\/refine\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/k3ylabs.com\\\/research-development\\\/projects\\\/refine\\\/\"},\"author\":{\"name\":\"k3y news\",\"@id\":\"https:\\\/\\\/k3ylabs.com\\\/#\\\/schema\\\/person\\\/9c622781378c531311096a78feb83f04\"},\"headline\":\"REFINE\",\"datePublished\":\"2025-01-26T10:52:12+00:00\",\"dateModified\":\"2025-07-02T10:34:56+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/k3ylabs.com\\\/research-development\\\/projects\\\/refine\\\/\"},\"wordCount\":9,\"image\":{\"@id\":\"https:\\\/\\\/k3ylabs.com\\\/research-development\\\/projects\\\/refine\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/k3ylabs.com\\\/wp-content\\\/uploads\\\/2025\\\/01\\\/REFINE_logo.png\",\"articleSection\":[\"Project\"],\"inLanguage\":\"el\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/k3ylabs.com\\\/research-development\\\/projects\\\/refine\\\/\",\"url\":\"https:\\\/\\\/k3ylabs.com\\\/research-development\\\/projects\\\/refine\\\/\",\"name\":\"REFINE - 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