TropiCam-AI from MNCN-CSIC identifies Amazonian species with 95% accuracy, optimizing wildlife monitoring

The technological advancement in species conservation has taken a new turn with TropiCam-AI, a system that identifies species in the Amazon with an impressive accuracy of 95%. Developed by the National Museum of Natural Sciences (MNCN-CSIC), this tool automates the analysis of images captured by camera traps in the canopy of tropical forests, redefining wildlife monitoring in ecosystems as biodiverse as the Amazon.

TropiCam-AI: Innovation in Amazonian Species Identification

TropiCam-AI’s ability to recognize 84 taxa of neotropical mammals and birds, including all genera of New World monkeys, transforms biodiversity research. This system optimizes image classification in seconds, thus improving the efficiency in the study of species distribution and facilitating the creation of accurate and updated databases.

Historically, species monitoring required exhaustive manual work by biologists, a method prone to errors and time-consuming. Now, TropiCam-AI automates the process, allowing efficient analysis of images and data, which is crucial for the study of wildlife in unexplored areas.

The introduction of TropiCam-AI represents a significant advancement by enabling the identification of species even difficult to observe through traditional methods. This tool has been trained with over 180,000 camera trap images from regions such as Brazil and Peru, in addition to 54,000 citizen science images from the iNaturalist platform.

To increase accuracy, a hierarchical classification strategy has been implemented, assigning difficult-to-identify species to higher levels such as genus or family. This allows the model to function even in habitats and species not included during the initial training.

Furthermore, TropiCam-AI is available on the AddaxAI platform, facilitating access for researchers and expanding the use of artificial intelligence in the study of neotropical biodiversity. This accessibility promotes the development of faster and more accurate studies in ecology and conservation.

In conclusion, TropiCam-AI not only accelerates the pace of scientific research but also democratizes access to artificial intelligence, becoming an essential ally in protecting biodiversity in the Amazon. This advancement promises to revolutionize the way we understand and preserve one of the planet’s richest ecosystems.