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Interactive Plant Species Identification with Mobile Devices Max Planck Institute for Biogeochemistry www.floraincognita.com Motivation Global biodiversity is rapidly declining Previous Research & Scientists and NGOs raise alarm about the decreasing species knowledge in our society • Technological research mainly focussed on fully automated species classification through image recognition with debatable achievements • Educational research focussed mainly on supporting decisions on dichotomous keys by example images, drawings, and simplified explanations but keeping the traditional sequence of dichotomous keys United Nations (UN) propagate a decade (2011–2020) of biodiversity to raise social awareness for the importance of biodiversity and the responsibility for an sustainable life-style Plant species identification today • requires using a sequence of dichotomous keys Timeliness of the Problem • is often challenging and time consuming for botanists and is almost impossible for non-botanists • Constant availability of portable devices incorporating a myriad of precise sensors provides the basis for more sophisticated ways of guiding and assissting people in species identification Project Goals and Approach • Approaching trends and technologies such as augmented reality, data glasses, or 3D scans give this research topic a long-term perspective • Developing a semi-automated user-interactive plant species identification process and application for mobile devices On-site and real-time identification of plant species with mobile devices Flora Incognita server with species and traits repository (3) Query additional sources for corresponding habitat information (2) Transferring image and meta-data Mobile devices with wireless internet connection (e.g., position, direction, date, device type, user type) to the project server External data sources: land use and habitat maps, geological maps, species distribution data, phenological data (4) [Iteratively] Determining most relevant trait and prompting the user for its acquisition (e.g., „mark the flower in the image“, „take additional picture of special plant part“, „check for thorns“) (1) Taking an initial image of the plant through the project app User with mobile device and project app (6) [Upon Match] Record traits in research data repositories, log match in databases of nature conservation authorities (5) [Upon Match] Send species details to device Databases of nature conservation authorities Research data repositories Work Areas at the MPI-BGC Area I: Plant traits repository and image dataset Project Facts • Development and implemenation of a repository covering characteristic plant traits • Analysing plant traits variability via literature research and field investigations • Set up a standardised image dataset for testing and evaluating image processing methods Duration: 2014–2019 Collaborators and Partners Area II: Incremental plant identification process & prototype evaluation • Development and realization of an incremental, semi-automatic plant identification process • Developement of didactically optimized user interactions during the classification process • Development and realization of user studies to evaluate the difficulty and the accuracy of manually determined plant traits • Detailed evaluation of the prototype application with different user groups Funded by Area III: Field mapping system and user platform • Development of strategies and requirements for an automated field mapping system (Partner: TLUG) • Development of strategies and requirements for platform to involve interested professional and hobby botanists Jana Wäldchen Michael Rzanny Angelika Thuille Ernst-Detlef Schulze Patrick Mäder Marco Seeland Nedal Alaqraa Funding: ~1.92M € (total) Nils Würfel David Wiesner