WildTrails

Homepage
Hiking Recommendations
Hiking Donations
Hiking posts

Inspiration

We drew inspiration from the growing need to balance outdoor recreation with ecological responsibility. Seeing the impact of climate change on wildlife, we wanted to create a platform that encourages both enjoyment of nature and active conservation efforts.

What It Does

WildTrails is a hiking app that uses AI to recommend trails based on weather, safety, and popularity data. It fosters a community around wildlife sightings—users earn points for sharing photos of local fauna, learn about endangered species, and can donate directly to relevant conservation organizations.

How We Built It

Backend (Python + Flask): Integrates Google Maps, WeatherAPI, and safety data to power an AI/ML model for dynamic trail recommendations.

Frontend (TypeScript/TSX): Displays trail info, user posts, and donation links in a responsive UI. Community & Gamification: Points and badges for wildlife sightings, encouraging responsible exploration and awareness of at-risk species.

Accomplishments We’re Proud Of

Seamless API integration and data fusion to deliver real-time trail recommendations. An interactive community feature that not only rewards wildlife sightings but also teaches users about each species and its conservation status. A clear path to impact with built-in donation options and educational prompts. What’s Next for WildTrails

Advanced AI Verification: Implement computer vision to identify species from photos and award points automatically. Expanded Conservation Partnerships: Collaborate with local NGOs and parks to offer volunteer opportunities within the app. Global Trail Coverage: Extend beyond initial regions to support more countries and varied ecosystems. Refined Gamification: Introduce team challenges, seasonal events, and more in-depth achievements to sustain long-term engagement.

Built With

Submitted to

CalgaryHacks 2025

Created by

I mostly worked on the socketing for the server and client, as well as making the server, ARGOS. This server takes in data from several APIs including Google Maps/Reviews, Weather, Canada Emergency Alerts, and then uses a pseudo-machine learning algorithm to calculate the top 100 sites for the user to visit. We then upload that data, with the preferences to Google Gemini to filter the top 15 sites.

Chetas Patel
I contributed to WildTrails by helping develop the AI-based trail recommendation system and wildlife community features. I worked on the Python + Flask backend to integrate Google Maps, WeatherAPI, and safety data into our recommendation pipeline, and helped structure models for user posts and wildlife sightings. I also supported the frontend by building TSX components for trail details, sightings, and donation flows, and collaborated on the points/badges system to promote conservation-focused engagement. Overall, I focused on creating a reliable, user-friendly experience that connects outdoor exploration with environmental responsibility.

Dilraj Kingra
I focused on the business aspects of WildTrails, drawing inspiration from the urgent need to balance outdoor recreation with ecological responsibility. My contribution included identifying market opportunities and fostering partnerships with conservation organizations. My goal was to ensure that WildTrails not only enhances hiking experiences but also contributes meaningfully to wildlife preservation.

Alvi Zaman
Monil Patel
Subeg Chahal

Updates

Chetas Patel started this project — Feb 16, 2025 01:27 PM EST

Leave feedback in the comments!

Log in or sign up for Devpost to join the conversation.