Have you ever been strolling around town and been taken aback by a beautiful, yet unknown flower or tree that you just don’t know the name of? Pl@ntNet is there to help by comparing submitted pictures to a vast database of almost 2 million submissions by citizen scientists around the world. The app is available for iPhones and Androids and simply requires you to take a picture of the plant you are curious about. The app then pulls up a list of possible species so that you can best assess which species your mysterious plant is. Pl@ntNet is a citizen science project that began in 2009 with the support of the Agropolis Foundation with the goal of engaging citizen scientists in the logging of global biodiversity. In addition to providing identification tools for users, the dataset that images are added to augment projects being conducted around the globe. There are 22 biodiversity logging projects currently underway, 16 geographical projects, 3 thematic projects on ornamental and cultivated plants, and 3 micro-projects. There are questions surrounding the accuracy of plant identification, given that the user has to choose amongst the options generated from the Pl@ntNet app. Despite citizen scientists having to make a determination without verified expertise, it is certainly an engaging project with the admirable goal of making knowledge more accessible to the everyday nature enthusiast.

Heredia, Ignacio. “Large-scale plant classification with deep neural networks.”


Biodiversity, Citizen Science, Data, Ecological Monitoring, Internet of Things, Visual Technologies