TrackTagger

TrackTagger is a mobile + web citizen-science app for logging animal signs (tracks, scat, feathers, scratch marks) with a focus on verification and usefulness to conservation teams. Users capture photos with a simple scale guide, auto-collect GPS/time/weather, and answer a short standardized checklist (substrate, gait, nearby habitat). An AI model suggests likely species but forces a confidence rating and provides “what to photograph next” prompts to reduce junk submissions. Submissions enter a review queue where trained volunteers and partner biologists verify records, then export validated sightings to common conservation formats. The app also supports offline field mode, route recording, and “monitoring missions” (e.g., monthly transects) so data becomes repeatable rather than random. The realistic value is not novelty—it’s higher-quality, lower-noise data that agencies can actually use.