WildDex

A wildlife encounter tracking application that gamifies conservation data collection, created at Calgary Hacks 2025.

Overview

WildDex transforms wildlife encounters into memorable experiences while contributing to conservation efforts. Inspired by Pokémon, users can "capture" wildlife sightings using their smartphone, creating their personal wildlife index while helping researchers track animal habits and patterns.

Features

• Image-based wildlife identification using machine learning
• Geolocation tracking for wildlife encounters
• Community feed for sharing discoveries
• Achievement system with special badges
• Secure user authentication
• Interactive map integration

Installation

Prerequisites

• Docker Desktop
• Node.js
• npm

Setup

1. Clone the repository

git clone https://github.com/suxxmjz/calgary-hacks-2025

2. Install dependencies in both client and server directories

cd virtual-pokeball && npm install
cd ../server && npm install

3. Start the application

docker compose up --build

Technology Stack

• Frontend: React
• Backend: Node.js
• Database: PostgreSQL
• Authentication: Clerk
• Storage: Supabase
• Machine Learning: TensorFlow
• Maps: Google Maps API
• Containerization: Docker

Technical Implementation

Machine Learning Model

Our image classification system uses TensorFlow to identify wildlife species. The model has been fine-tuned to handle various wildlife categories, focusing on accuracy and real-world application.

Data Storage

• PostgreSQL database for application data
• Supabase bucket for image storage and retrieval
• Secure user data management through Clerk

Location Services

Integrated Google Maps API enables precise geo-tagging of wildlife encounters, contributing to valuable location-based data for conservation research.

Challenges Overcome

• Developed sophisticated image classification models capable of identifying multiple species
• Successfully deployed machine learning models in a production environment
• Integrated complex systems including authentication, storage, and mapping services

Future Development

• Research portal for authorized users to access wildlife sighting data
• Enhanced classification capabilities for more species
• Extended geographical coverage
• Advanced analytics for conservation researchers

Team Achievements

• Created an intuitive and user-friendly interface
• Successfully integrated multiple complex technologies
• Developed a practical solution for wildlife conservation data collection
• Implemented secure and scalable architecture

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WildDex: Turning wildlife encounters into conservation data, one capture at a time.