WildTrack

About

Key Features

• Footprint Identification Technology (FIT): Award-winning AI pipeline that identifies species, individual animals, foot type, sex, and age from footprint images without disturbing wildlife.
• Community-Based Mobile Data Collection: A mobile app enables citizen scientists and local communities to collect and submit footprint data from the field to the global AI training database.
• Traditional Ecological Knowledge Integration: Combines indigenous and community-based ecological knowledge with modern AI for culturally sensitive and scientifically rigorous monitoring.
• Multi-Species Algorithm Library: Over 41 species algorithms covering endangered mammals across diverse ecosystems and continents, with continuous expansion.
• Drone & Landscape-Scale Monitoring: Supports drone-based data collection and AI analysis for large-scale habitat and population monitoring across vast territories.

Use Cases

• Wildlife biologists non-invasively monitoring endangered mammal populations without capture-and-tag stress or equipment costs
• Conservation organizations tracking and mitigating human-wildlife conflict using real-time lion and leopard footprint data
• Universities and research institutions integrating AI footprint analysis into biodiversity and ecology field studies
• Citizen scientists and indigenous communities contributing local footprint data via mobile app to global conservation AI models
• Environmental NGOs conducting landscape-scale drone and ground-based wildlife surveys across remote or protected habitats

Pros

• Truly Non-Invasive: Requires no animal capture, tagging, or handling — dramatically reducing stress on wildlife while enabling continuous population monitoring.
• Global Reach: Deployed across 20+ countries on 5 continents, supported by 15 partner universities and a dedicated network of volunteer scientists.
• Accessible to All Skill Levels: The free mobile app allows anyone — from professional researchers to everyday citizens — to meaningfully contribute to conservation data collection.
• World-First AI Pipeline: WildTrack built the first AI-based footprint identification system for endangered species, validated by international research and award recognition.

Cons

• Footprint-Only Methodology: Exclusively focuses on footprint-based identification, which may not be suitable for species or habitats where clear footprints are difficult to obtain.
• Community Data Dependency: AI model accuracy relies on the quality and volume of footprint images submitted by the community, which can vary by region and contributor experience.
• Non-Profit Resource Limitations: As a donation-funded nonprofit, feature development and species algorithm expansion may progress more slowly than commercially backed platforms.