{"id":39467,"date":"2022-12-15T18:03:50","date_gmt":"2022-12-15T18:03:50","guid":{"rendered":"https:\/\/www.vmengine.net\/2022\/12\/15\/aws-in-space-how-we-collect-and-analyze-data-in-orbit\/"},"modified":"2025-05-23T17:34:22","modified_gmt":"2025-05-23T17:34:22","slug":"aws-in-space-how-we-collect-and-analyze-data-in-orbit","status":"publish","type":"post","link":"http:\/\/temp_new.vmenginelab.com\/en\/2022\/12\/15\/aws-in-space-how-we-collect-and-analyze-data-in-orbit\/","title":{"rendered":"AWS in space: how we collect and analyze data in orbit"},"content":{"rendered":"<div class=\"et_pb_section et_pb_section_458 et_section_regular\" >\n<div class=\"et_pb_row et_pb_row_556\">\n<div class=\"et_pb_column et_pb_column_4_4 et_pb_column_562  et_pb_css_mix_blend_mode_passthrough et-last-child\">\n<div class=\"et_pb_module et_pb_text et_pb_text_2199  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<p>Only 10 months was enough for<strong><br \/>\n  <a href=\"https:\/\/aws.amazon.com\/it\/?nc2=h_lg\"> Amazon Web Service<\/a><br \/>\n<\/strong>, the global<strong> Cloud Computing<\/strong> giant, to test a fast and efficient method to collect and analyze data directly in orbit using the Cloud. Thus, the company announced that it had successfully run a <strong>suite of computing<\/strong> and <strong>machine learning<\/strong> software on a<em> satellite<\/em>.<\/p>\n<\/div><\/div>\n<div class=\"et_pb_module et_pb_cta_593 et_pb_promo  et_pb_text_align_center et_pb_bg_layout_light\">\n<div class=\"et_pb_promo_description et_multi_view_hidden\"><\/div>\n<div class=\"et_pb_button_wrapper\"><a class=\"et_pb_button et_pb_promo_button\" href=\"https:\/\/temp_new.vmenginelab.com\/?s=spazio\" target=\"_blank\">Edge Computing, AWS to conquer space<\/a><\/div>\n<\/p><\/div>\n<div class=\"et_pb_module et_pb_image et_pb_image_612\">\n<p>\t\t\t\t<span class=\"et_pb_image_wrap \"><img decoding=\"async\" src=\"http:\/\/temp_new.vmenginelab.com\/wp-content\/uploads\/2022\/12\/space-satellite-2.jpg\" alt=\"\" title=\"Space satellite orbiting the earth. Elements of this image furnished by NASA.\"  sizes=\"(max-width: 740px) 100vw, 740px\" class=\"wp-image-35645\" \/><\/span>\n\t\t\t<\/div>\n<div class=\"et_pb_module et_pb_text et_pb_text_2200  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<p>This is a truly amazing result because this experiment has made it possible <strong>to analyze huge volumes of raw satellite data in orbit<\/strong> and <strong>to transmit to the ground only those most useful<\/strong> for archiving or further analysis. This reduces costs and, above all, makes decisions much more promptly.<\/p>\n<\/div><\/div>\n<div class=\"et_pb_module et_pb_text et_pb_text_2201  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<p>But what did <strong>the experiment implemented by<\/strong> <strong>AWS<\/strong> consist of? In essence, the operation was focused on <strong>applying various machine learning models<\/strong> to data captured by the satellite&#8217;s sensors to<strong> identify specific objects<\/strong> both in the sky, such as clouds and fire smoke, and on the ground, including buildings and ships. Raw satellite imagery and datasets like this are usually quite large. So engineers created a way to break up large data files into smaller ones. Using<strong> AWS<\/strong> <strong>AI<\/strong> <strong> services helps <strong>reduce image size by up to 42%,<\/strong> increasing processing speeds and enabling<strong> real-time inference in orbit<\/strong>.<\/strong> In short, a truly revolutionary experiment.<\/p>\n<\/div><\/div>\n<div class=\"et_pb_module et_pb_text et_pb_text_2202  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<p>To reiterate the importance and essentiality of this experiment is the vice president of <a href=\"https:\/\/aws.amazon.com\/it\/?nc2=h_lg\"><br \/>\n  <strong>Amazon Web Service<\/strong><br \/>\n<\/a> <strong>Max Peterson<\/strong> who explained that using<strong> AWS software to perform real-time data analysis on board a satellite<\/strong>, and send this analysis directly through the <strong>Cloud<\/strong>, is a decisive change in existing approaches to space data management. <em>&#8220;It also helps<\/em> to <em>push the boundaries of what we believe is possible for satellite operations,&#8221;<\/em> Max Peterson said.<\/p>\n<\/div><\/div>\n<div class=\"et_pb_module et_pb_cta_594 et_pb_promo  et_pb_text_align_center et_pb_bg_layout_light\">\n<div class=\"et_pb_promo_description et_multi_view_hidden\"><\/div>\n<div class=\"et_pb_button_wrapper\"><a class=\"et_pb_button et_pb_promo_button\" href=\"https:\/\/temp_new.vmenginelab.com\/en\/2022\/12\/15\/aws-here-are-all-the-news-of-the-reinvent-2022\/\" target=\"_blank\">AWS, here are all the news of the re:Invent 2022<\/a><\/div>\n<\/p><\/div>\n<div class=\"et_pb_module et_pb_image et_pb_image_613\">\n<p>\t\t\t\t<span class=\"et_pb_image_wrap \"><img decoding=\"async\" src=\"http:\/\/temp_new.vmenginelab.com\/wp-content\/uploads\/2022\/12\/space-2-2.jpg\" alt=\"\" title=\"space 2\"  sizes=\"(max-width: 740px) 100vw, 740px\" class=\"wp-image-35649\" \/><\/span>\n\t\t\t<\/div>\n<div class=\"et_pb_module et_pb_text et_pb_text_2203  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<p>Suffice it to say that right now, despite research and technological progress, there are many technical challenges associated with storing and communicating data in space. What is it specifically? First of all,<strong> the high latency<\/strong>, i.e. the <strong>response time between round trips and the limited bandwidth<\/strong>. Even in this case, however, <strong>AWS<\/strong> is doing everything to innovate and overcome the obstacle, such as collaborating with <a href=\"https:\/\/www.dorbit.space\/\"><br \/>\n  <strong>D-Orbit <\/strong><br \/>\n<\/a>and <a href=\"https:\/\/unibap.com\/\"><br \/>\n  <strong>Unibap<\/strong><br \/>\n<\/a> to directly address these challenges that apply to <strong>satellite operations<\/strong>. These are two specialized companies, respectively Italian and Swedish, which have already experimented with previous collaborations in the past.<\/p>\n<\/div><\/div>\n<div class=\"et_pb_module et_pb_text et_pb_text_2204  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<p>But who are these two companies? <strong>D-Orbit<\/strong> is a member of the <a href=\"https:\/\/aws.amazon.com\/it\/partners\/\"><br \/>\n  <strong>AWS Partner Network<\/strong><br \/>\n<\/a> and, as we wrote, is an Italian company based in the province of Como. By applying <strong><a href=\"https:\/\/aws.amazon.com\/it\/machine-learning\/\">AWS compute and ML<\/a> <\/strong><strong>services<\/strong> to Earth observation imagery, <strong>D-Orbit<\/strong> was able to quickly analyze large amounts of data directly aboard the<a href=\"https:\/\/www.dorbit.space\/launch-deployment\"><strong> in-orbit ION satellite<\/strong><\/p>\n<p><\/a>. It allows a <strong>mechanical and electrical interface<\/strong>, thus ensuring the integration of on-board experiments and their management from the ground as a subsystem of <strong>ION<\/strong> itself.<\/p>\n<\/div><\/div>\n<div class=\"et_pb_module et_pb_cta_595 et_pb_promo  et_pb_text_align_center et_pb_bg_layout_light\">\n<div class=\"et_pb_promo_description et_multi_view_hidden\"><\/div>\n<div class=\"et_pb_button_wrapper\"><a class=\"et_pb_button et_pb_promo_button\" href=\"https:\/\/temp_new.vmenginelab.com\/2022\/11\/18\/cloud-aws-ancora-leader-nel-quadrante-magico-di-gartner\/\" target=\"_blank\">Cloud, AWS still a leader in Gartner&amp;apos;s &quot;Magic Quadrant<\/a><\/div>\n<\/p><\/div>\n<div class=\"et_pb_module et_pb_image et_pb_image_614\">\n<p>\t\t\t\t<span class=\"et_pb_image_wrap \"><img decoding=\"async\" src=\"http:\/\/temp_new.vmenginelab.com\/wp-content\/uploads\/2022\/12\/foto-space-ion-2.jpg\" alt=\"\" title=\"Photo Space Ion\"  sizes=\"(max-width: 600px) 100vw, 600px\" class=\"wp-image-35654\" \/><\/span>\n\t\t\t<\/div>\n<div class=\"et_pb_module et_pb_text et_pb_text_2205  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<p><strong>Sergio Mucciarelli<\/strong>, vice president of commercial sales at D-Orbit explained how customers want to securely process ever-increasing amounts of satellite data with very low latency. <em>&#8220;We believe in pushing towards edge computing, and this can only be done with space infrastructure that is fit for purpose,&#8221;<\/em> Mucciarelli said.<br \/>Unibap, also an <strong>AWS<\/strong> partner, is a Swedish high-tech company, which has created a<strong> space-qualified computing payload<\/strong>. The payload was then integrated onto the ION satellite and launched into space. On January 21, the team made the first successful contact with the<strong> payload<\/strong>, and executed the first remote command from Earth. And <strong>Fredrik Bruhn<\/strong>, chief evangelist in digital transformation and co-founder of <strong>Unibap<\/strong>, underlined how his company wants to<em> &#8220;help customers quickly transform raw satellite data into information that can be used in seconds, enable federated learning on board for autonomous information acquisition and increase the value of data that is transmitted downlink&#8221;.<\/em><\/p>\n<\/div><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"<p>An experiment that lasted 10 months: &#8220;A suite of calculation and machine learning software successfully executed&#8221;<\/p>\n","protected":false},"author":6,"featured_media":35629,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[97,3574],"tags":[71,4146,72,3464,5062,4846,4874,4953,4907,4954,4908,4955,4909],"class_list":["post-39467","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog-en","category-in-evidence","tag-amazon-web-services","tag-artificial-intelligence-en-2","tag-aws","tag-d-orbit","tag-intelligenza-artificiale-3","tag-machine-learning","tag-machine-learning-en","tag-satellite-en","tag-satellite","tag-space-en-2","tag-spazio","tag-unibap-en","tag-unibap"],"aioseo_notices":[],"jetpack_featured_media_url":"http:\/\/temp_new.vmenginelab.com\/wp-content\/uploads\/2022\/12\/nasa-nasa-gifs-1.gif","amp_enabled":true,"_links":{"self":[{"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/posts\/39467","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/comments?post=39467"}],"version-history":[{"count":1,"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/posts\/39467\/revisions"}],"predecessor-version":[{"id":41762,"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/posts\/39467\/revisions\/41762"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/media\/35629"}],"wp:attachment":[{"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/media?parent=39467"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/categories?post=39467"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/temp_new.vmenginelab.com\/en\/wp-json\/wp\/v2\/tags?post=39467"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}