Pl@ntNet is a citizen science platform designed to facilitate plant identification through user-submitted photographs. Its primary function is to help individuals identify plant species by analyzing images, contributing to broader plant biodiversity research efforts. The platform is structured to encourage public participation, inviting users to create accounts, submit plant observations, and collaborate in reviewing and correcting species identifications.
The system employs an AI-based tool to process and identify plants from images, with a collaborative review process involving expert users to maintain and improve accuracy. Pl@ntNet supports community-driven microprojects, which can focus on specific geographical areas or thematic collections of plants, allowing for targeted data collection and research. The platform also provides resources such as open data sets and an API for developers, supporting integration with external research projects and broader scientific initiatives.
Pl@ntNet is accessible as an application, and its website highlights its role in educational outreach, training sessions, and scientific collaborations. The platform is open and free for public use, relying on donations and partnerships for support. The Pl@ntNet trademark is owned by CIRAD, INRAE, INRIA, and IRD, and the platform is recognized as a contributor to international research and biodiversity monitoring projects.
By combining AI-driven plant identification with citizen science participation, Pl@ntNet addresses the need for accessible, large-scale plant species documentation and supports ongoing research in plant biodiversity.
In the Education & learning space, Pl@ntNet takes a focused approach. Helping users identify plants and contribute to biodiversity research through photo-based identification. It is built as an open-source project for nature enthusiasts. Pl@ntNet costs nothing to use. It ships for the web, iOS, and Android.
Key capabilities include plant identification, photo upload, and citizen science participation. The interface is available in English and French. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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