SBIR Phase I: High-throughput 3-D Insect Data Capture Enabling Large Scale Specimen Digitization and Machine Species Identification

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This Small Business Innovation Research (SBIR) Phase I is directed toward high-throughput roboticimaging and data capture of 3D physical insect specimens with applications to national intelligence andsecurity, vector epidemiology, agriculture, biodiversity research, and museum curation. Natural historymuseums are vast, largely untapped sources of biological data for addressing complex questions rangingfrom tracking terrorists to climate change. Yet ~1 billion U.S. specimens remain in museum drawers andcabinets, their characteristics, associated data, and even their existence hidden. Insects preserved onpins represent a significant proportion, with the ten largest collections housing over 100 million. While thescope of collections is immense, the expertise needed to identify insects of importance is in decline astaxonomists retire and university positions close. For some insect groups, few or no experts remaincapable of identifying species. The proposed technology will radically accelerate the pace of insectspecimen digitization. It will capture critical data from museum specimens and revitalize taxonomy byproviding datasets for computer-automated insect identification efforts. The project demonstrates robotichandling of pinned specimens is feasible, enabling a high-throughput system capable of manipulatingpinned specimens, partitioning the 3D scene, photographing specimens, and extracting databaseinformation with OCR rendering of specimen labels.The broader impact/commercial potential of this project spans myriad applications. Insects vectorimportant diseases of humans, livestock, and crops. Annually, malaria is implicated in a million humandeaths worldwide and aphids and their viruses cost US farmers over one billion dollars. New invasiveinsects regularly arrive on our shores undetected. Insects also have forensics applications, locatingevents in time and place and calculating times of death. Tools to quickly and efficiently identify insectshave immediate application in vector epidemiology, agricultural and environmental monitoring, bordersecurity and port inspection, law enforcement, and intelligence. Spatial-temporal data associated withfield collection of insect specimens are crucial for geolocation forensics, tracking climate change andrange expansion of invasive species, and locating geographic sources of potential biological controlagents for exotic pests. Current technologies and specimen digitization practices take too much time, costtoo much money, and simply cannot image most specimens. Semi-automated systems address onlymicroscope slide- or paper-mounted specimens. Currently no technology exists to even partiallyautomate the digitization of individual pinned insect specimens. Potential customers include insectcollections, museums, agribusinesses, epidemiologists, and agents in homeland security, port inspection,environmental monitoring, and national intelligence. Enormous secondary commercial potential existswith value-added online databases.