Product Overview: Pl@ntNet
Introduction
Pl@ntNet is a groundbreaking citizen science platform designed to facilitate the identification and inventory of plant species using advanced artificial intelligence (AI) and deep learning technologies. Founded in 2010 by a consortium of four French research organizations (CIRAD, Inria, INRAE, and IRD), Pl@ntNet has evolved into one of the world’s largest biodiversity observatories, with contributions from several million users across over 200 countries.
Key Features and Functionality
Plant Identification
Pl@ntNet allows users to identify plants simply by taking a photo of them using their smartphones or through the web application. The platform leverages deep learning algorithms to analyze the images and provide accurate identifications from a vast database of tens of thousands of plant species.
Community-Driven
The platform operates on a cooperative learning principle, where users can share their observations, which are then reviewed by the community. This collective effort enhances the AI’s ability to recognize plants, with more expert users having a greater influence on the validation process.
Multi-Platform Accessibility
Pl@ntNet is available on multiple platforms, including Android, iOS, and a web version, ensuring widespread accessibility for users worldwide.
Automated Identification and Validation
The platform uses AI to automatically identify plants from user-submitted photos. Only observations with a high confidence level (typically above 0.9) are considered valid and added to the public database, which is regularly updated to improve the AI’s performance.
Geolocated Data Collection
Pl@ntNet collects geolocated plant data, which is crucial for research purposes and helps in mapping plant distributions globally. This data is stored in a robust database that handles hundreds of millions of documents efficiently.
API Integration
For developers, Pl@ntNet offers an API (Pl@ntNet-API) that allows integration of the visual identification engine into other applications. This service is highly scalable, monitors quality of service, and includes automated rejection of inappropriate content, ensuring a seamless user experience.
Data Management and Scalability
To handle the rapidly growing volume of data (doubling every year since 2015), Pl@ntNet utilizes ArangoDB, a document-oriented database with SQL-like queries. This solution enables fast and complex queries at scale, reduces storage needs, and enhances overall performance and efficiency.
Benefits and Impact
- Enhanced Biodiversity Monitoring: Pl@ntNet contributes significantly to global biodiversity monitoring by collecting and analyzing vast amounts of geolocated plant data.
- Community Engagement: The platform fosters a collaborative environment where citizens, researchers, and botanists work together to improve plant identification and knowledge.
- Continuous Improvement: Regular re-training of the AI using community-reviewed observations ensures that the identification quality and the number of recognized species are continually improved.
- Scalable and Efficient: The use of advanced database solutions like ArangoDB ensures that the platform can handle high data volumes and complex queries efficiently.
In summary, Pl@ntNet is a powerful tool for plant identification, driven by AI, community engagement, and robust data management. It serves as a valuable resource for both the general public and the scientific community, contributing significantly to our understanding and conservation of plant biodiversity.