{"id":2392,"date":"2022-12-12T11:14:31","date_gmt":"2022-12-12T15:14:31","guid":{"rendered":"https:\/\/ece.ncsu.edu\/?p=255720"},"modified":"2022-12-12T11:14:31","modified_gmt":"2022-12-12T15:14:31","slug":"fossil-sorting-robots-will-help-researchers-study-oceans-climate","status":"publish","type":"post","link":"https:\/\/my.ece.ncsu.edu\/communications\/2022\/fossil-sorting-robots-will-help-researchers-study-oceans-climate\/","title":{"rendered":"Fossil-Sorting Robots Will Help Researchers Study Oceans, Climate"},"content":{"rendered":"<div class=\"featured-img\"><img width=\"1500\" height=\"844\" src=\"https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500.webp\" class=\"attachment-full size-full wp-post-image\" alt=\"\" style=\"margin-bottom: 15px;\" decoding=\"async\" loading=\"lazy\" srcset=\"https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500.webp 1500w, https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500-1280x720.webp 1280w, https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500-980x551.webp 980w, https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500-480x270.webp 480w\" sizes=\"auto, (min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) and (max-width: 1280px) 1280px, (min-width: 1281px) 1500px, 100vw\" \/><\/div>\n<p>Researchers have demonstrated a robot capable of sorting, manipulating, and identifying microscopic marine fossils. The new technology automates a tedious process that plays a key role in advancing our understanding of the world\u2019s oceans and climate \u2013 both today and in the prehistoric past.<\/p>\n<p>\u201cThe beauty of this technology is that it is made using relatively inexpensive off-the-shelf components, and we are making both the designs and the artificial intelligence software open source,\u201d says Edgar Lobaton, co-author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University. \u201cOur goal is to make this tool widely accessible, so that it can be used by as many researchers as possible to advance our understanding of oceans, biodiversity and climate.\u201d<\/p>\n<p>The technology, called Forabot, uses robotics and artificial intelligence to physically manipulate the remains of organisms called foraminifera, or forams, so that those remains can be isolated, imaged and identified.<\/p>\n<p>Forams are protists, neither plant nor animal, and have been prevalent in our oceans for more than 100 million years. When forams die, they leave behind their tiny shells, most less than a millimeter wide. These shells give scientists insights into the characteristics of the oceans as they existed when the forams were alive. For example, different types of foram species thrive in different kinds of ocean environments, and chemical measurements can tell scientists about everything from the ocean\u2019s chemistry to its temperature when the shell was being formed.<\/p>\n<p>However, evaluating foram shells and fossils is both tedious and time consuming. Which is why a team of engineering and paleoceanography experts developed Forabot to automate the process.<\/p>\n<p>\u201cAt this point, Forabot is capable of identifying six different types of foram, and processing 27 forams per hour \u2013 but it never gets bored and it never gets tired,\u201d Lobaton says. \u201cThis is a proof-of-concept prototype, so we\u2019ll be expanding the number of foram species it is able to identify. And we\u2019re optimistic we\u2019ll also be able to improve the number of forams it can process per hour.<\/p>\n<p>\u201cAlso, at this point, the Forabot has an accuracy rate of 79% for identifying forams, which is better than most trained humans.\u201d<\/p>\n<p>\u201cOnce Forabot has been optimized, it will be a valuable piece of research equipment, allowing student \u2018foram pickers\u2019 to better spend their time learning more advanced skills,\u201d says Tom Marchitto, co-author of the paper and a professor of geological sciences at the University of Colorado, Boulder. \u201cBy using community-sourced taxonomic knowledge to train the robot, we can also improve uniformity of foram identification across research groups.\u201d<\/p>\n<p>Here\u2019s how Forabot works. First, users have to wash and sieve a sample of hundreds of forams. This leaves users with a pile of what looks like sand. The sample of forams is then placed into a container called the isolation tower. A needle at the bottom of the isolation tower then projects up through the sample, lifting a single foram up where it is removed from the tower via suction. The suction pulls the foram to a separate container called the imaging tower, which is equipped with an automated, high-resolution camera that captures multiple images of the foram. After the images are taken, the foram is again lifted by a needle until it can be picked up via suction and deposited in the relevant container in a sorting station.<\/p>\n<p><iframe loading=\"lazy\" title=\"Foram Imaging Robot\" width=\"1080\" height=\"608\" src=\"https:\/\/www.youtube.com\/embed\/nLkLIghc4Jg?feature=oembed\"  allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe><\/p>\n<p>\u201cThe idea is that our AI can use the images to identify what type of foram it is, and sort it accordingly,\u201d Lobaton says.<\/p>\n<p>\u201cWe\u2019re publishing in an open source journal, and are including the blueprints and AI software in the supplementary materials to that paper,\u201d Lobaton adds. \u201cHopefully, people will make use of it. The next step for us is to expand the types of forams the system can identify, and work on optimizing the operational speed.\u201d<\/p>\n<p>The paper, \u201c<a href=\"https:\/\/agupubs.onlinelibrary.wiley.com\/doi\/full\/10.1029\/2022GC010689\"  rel=\"noopener\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/agupubs.onlinelibrary.wiley.com\/doi\/full\/10.1029\/2022GC010689&amp;source=gmail&amp;ust=1670936559238000&amp;usg=AOvVaw2wV_FchlrAx9cLSiXNwWdZ\">Forabot: Automated Planktic Foraminifera Isolation and Imaging<\/a>,\u201d is published in the open-access journal\u00a0<em>Geochemistry, Geophysics, Geosystems<\/em>. Corresponding author of the paper is Turner Richmond, a recent Ph.D. graduate from NC State. The paper was co-authored by Jeremy Cole, a Ph.D. graduate of NC State; and by Gabriella Dangler, an undergraduate at NC State.<\/p>\n<p>The work was done with support from the National Science Foundation, under grant number 1829930.<\/p>\n","protected":false},"excerpt":{"rendered":"<div class=\"featured-img\"><img width=\"1500\" height=\"844\" src=\"https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500.webp\" class=\"attachment-full size-full wp-post-image\" alt=\"\" decoding=\"async\" loading=\"lazy\" srcset=\"https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500.webp 1500w, https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500-1280x720.webp 1280w, https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500-980x551.webp 980w, https:\/\/ece.ncsu.edu\/wp-content\/uploads\/2022\/12\/Lobaton-forabot-HEADER-1500-480x270.webp 480w\" sizes=\"auto, (min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) and (max-width: 1280px) 1280px, (min-width: 1281px) 1500px, 100vw\"><\/div>\n<p>New tech from Edgar Lobaton&#8217;s lab automates a tedious process that plays a key role in ocean and climate research.<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"ncst_dynamicHeaderBlockName":"","ncst_dynamicHeaderData":"","ncst_content_audit_freq":"","ncst_content_audit_date":"","ncst_content_audit_display":false,"ncst_backToTopFlag":"","footnotes":""},"categories":[180],"tags":[],"class_list":["post-2392","post","type-post","status-publish","format-standard","hentry","category-research"],"displayCategory":null,"acf":{"ncst_posts_meta_modified_date":null},"_links":{"self":[{"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/posts\/2392","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/comments?post=2392"}],"version-history":[{"count":1,"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/posts\/2392\/revisions"}],"predecessor-version":[{"id":2393,"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/posts\/2392\/revisions\/2393"}],"wp:attachment":[{"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/media?parent=2392"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/categories?post=2392"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/my.ece.ncsu.edu\/communications\/wp-json\/wp\/v2\/tags?post=2392"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}