{"id":15,"date":"2020-01-30T22:42:20","date_gmt":"2020-01-30T22:42:20","guid":{"rendered":"http:\/\/antidrones-project.org\/?page_id=15"},"modified":"2024-07-07T21:20:18","modified_gmt":"2024-07-07T21:20:18","slug":"project-overview","status":"publish","type":"page","link":"https:\/\/ai4cuav.org\/index.php\/project-overview\/","title":{"rendered":"Project Overview"},"content":{"rendered":"<div id=\"tdi_1\" class=\"tdc-zone\"><div class=\"tdc_zone tdi_2  wpb_row td-pb-row\"  >\n<style scoped>\n\/* custom css - generated by TagDiv Composer *\/\n\n\/* custom css - generated by TagDiv Composer *\/\n.tdi_2{\r\n                    min-height: 0;\r\n                }\n<\/style><div id=\"tdi_3\" class=\"tdc-row\"><div class=\"vc_row tdi_4  wpb_row td-pb-row\" >\n<style scoped>\n\/* custom css - generated by TagDiv Composer *\/\n\n\/* custom css - generated by TagDiv Composer *\/\n.tdi_4,\r\n                .tdi_4 .tdc-columns{\r\n                    min-height: 0;\r\n                }.tdi_4,\r\n\t\t\t\t.tdi_4 .tdc-columns{\r\n\t\t\t\t    display: block;\r\n\t\t\t\t}.tdi_4 .tdc-columns{\r\n\t\t\t\t    width: 100%;\r\n\t\t\t\t}.tdi_4:before,\r\n\t\t\t\t.tdi_4:after{\r\n\t\t\t\t    display: table;\r\n\t\t\t\t}\n<\/style><div class=\"vc_column tdi_6  wpb_column vc_column_container tdc-column td-pb-span12\">\n<style scoped>\n\/* custom css - generated by TagDiv Composer *\/\n\n\/* custom css - generated by TagDiv Composer *\/\n.tdi_6{\r\n                    vertical-align: baseline;\r\n                }.tdi_6 > .wpb_wrapper,\r\n\t\t\t\t.tdi_6 > .wpb_wrapper > .tdc-elements{\r\n\t\t\t\t    display: block;\r\n\t\t\t\t}.tdi_6 > .wpb_wrapper > .tdc-elements{\r\n\t\t\t\t    width: 100%;\r\n\t\t\t\t}.tdi_6 > .wpb_wrapper > .vc_row_inner{\r\n\t\t\t\t    width: auto;\r\n\t\t\t\t}.tdi_6 > .wpb_wrapper{\r\n\t\t\t\t    width: auto;\r\n\t\t\t\t    height: auto;\r\n\t\t\t\t}\n<\/style><div class=\"wpb_wrapper\" ><div class=\"td_block_wrap td_block_text_with_title tdi_7 tagdiv-type td-pb-border-top td_block_template_1\"  data-td-block-uid=\"tdi_7\" >\n<style>\n\/* custom css - generated by TagDiv Composer *\/\n.td_block_text_with_title{\r\n                  margin-bottom: 44px;\r\n                  -webkit-transform: translateZ(0);\r\n                  transform: translateZ(0);\r\n                }.td_block_text_with_title p:last-child{\r\n                  margin-bottom: 0;\r\n                }\n<\/style><div class=\"td-block-title-wrap\"><h4 class=\"block-title td-block-title\"><span class=\"td-pulldown-size\">Project Overview<\/span><\/h4><\/div><div class=\"td_mod_wrap td-fix-index\"><p>The current AI-based algorithms on detection and classification algorithms based on radar signatures (i.e. signals and images) shown a non-reliable solution for the detection and classification of small UAVs. A combined system with the EO\/IR detection and classification based on AI-techniques could improve the required performances.<\/p>\n<p><strong>Ai4CUAV<\/strong> intends to improve the <strong>Threat Evaluation Subsystem of a counter UAV (C-UAV) through AI-based algorithms<\/strong>. Supposing the anti-drones composed by multiple heterogenous sensors, such as radars and EO\/IR sensors, these algorithms \u201cwork\u201d on radar signals and EO\/IR images to enable the detection and classification of the killer-drones, as well as on drone trajectories to help to recognize a drone from another object.<\/p>\n<p>This projected will build a shared database of RF and EO\/IR signatures of different drones which can be used as training data and test set, which allows to compare different detection and classification techniques.<\/p>\n<p>Ai4CUAV will investigate all the key SOTA of AI techniques from multiple sensor sources, including but not limited to, machine learning and deep learning. These techniques will be evaluated against the different use cases and scenarios, in order to assess the most adapted\/promising ones. For the most promising techniques, algorithm prototyping and adaptation will be performed to assess preliminary performances through simulations.<\/p>\n<p>This project is a follow on of the <em>NATO SPS project n. G5633 \u201cANTI-DRONES \u2013 Innovative concept to detect, recognize and track killer-drones&#8221;<\/em>, involving the core partners CNIT-RASS (NPD) and MTU (Co-Director), that will be concluded in September 2022 with good results, focused on the development of a new concept of anti-drone system, based on mini-radar technology and signal processing, able to detect, recognize and track the killer-drones \u2013 mini\/micro UAS &#8211; in order to facilitate the neutralization of them minimizing the risk for people and assets. This <strong>AI-framework will be integrated into the ANTI-DRONES prototype, tested and evaluated by the end-user experts<\/strong>.<br \/>\n<figure id=\"attachment_472\" aria-describedby=\"caption-attachment-472\" style=\"width: 696px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-472 size-large\" src=\"https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-1024x369.png\" alt=\"AI4CUAV Conceptual Design\" width=\"696\" height=\"251\" srcset=\"https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-1024x369.png 1024w, https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-300x108.png 300w, https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-768x277.png 768w, https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-1536x553.png 1536w, https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-1166x420.png 1166w, https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-696x251.png 696w, https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1-1068x385.png 1068w, https:\/\/ai4cuav.org\/wp-content\/uploads\/2024\/07\/Conceptual-Design-1.png 1735w\" sizes=\"(max-width: 696px) 100vw, 696px\" \/><figcaption id=\"caption-attachment-472\" class=\"wp-caption-text\">Figure 1. AI4CUAV Conceptual Design<\/figcaption><\/figure><br \/>\nAI4CUAV project is a research project focused on a breakthrough innovation using AI. As such, it is expected to advance the accuracy of detection algorithms, and set forward AI-based solution of high complexity problems. From a prospect vision, Ai4CUAV would bring into market a novel and innovative AI application enabling intelligent ISR in complex situations.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/pages\/15"}],"collection":[{"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/comments?post=15"}],"version-history":[{"count":4,"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/pages\/15\/revisions"}],"predecessor-version":[{"id":473,"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/pages\/15\/revisions\/473"}],"wp:attachment":[{"href":"https:\/\/ai4cuav.org\/index.php\/wp-json\/wp\/v2\/media?parent=15"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}