PurePath

Inspiration

It’s common practice to check the weather before traveling, but weather alone doesn’t reflect the full picture of health safety. Factors like air quality, disease outbreaks, and environmental conditions can significantly impact a traveler’s well-being, yet this information is scattered and difficult to interpret. We were inspired to create PurePath to help people proactively protect their health by making invisible health risks visible and understandable before and during travel.

What it does

Users enter their destination, travel dates, and health needs, and PurePath generates a personalized health itinerary with daily risk scores based on:

Air quality
Disease outbreaks
Weather and environmental conditions
Historical health trends PurePath also features:
An interactive heatmap that visualizes health risk across locations in real time
A live outbreak tracker powered by continuously updated data
An AI chatbot that helps users plan itineraries, recommend safe activities, and suggest restaurants based on dietary restrictions

How we built it

We built PurePath by integrating multiple environmental and public health datasets from sources such as Kaggle and live APIs Our process included
Collecting and aggregating real-time and historical health and environmental data
Cleaning and filtering missing and inconsistent data to ensure reliability
Developing a predictive model to identify and visualize location-based health risks
Building an AI chatbot that allows users to interact with the data and receive personalized recommendations
Creating an interactive frontend that displays health risk heatmaps and personalized itineraries ## Challenges we ran into
One of our biggest challenges was working with real-world datasets that were incomplete and inconsistent
Cleaning and integrating multiple datasets into one usable system required significant preprocessing
Many data sets were AI! ## Accomplishments that we're proud of
We’re proud that we built a platform that transforms fragmented health and environmental data into a unified, predictive health intelligence system
Predictive respiratory model
Successfully integrated multiple real-time and historical datasets
Built an AI chatbot that generates personalized recommendations
Created an interactive heatmap visualization combining multiple risk factors
Developed a system that can proactively help users avoid health risks ## What we learned
Work with large real-world datasets
Clean and preprocess messy data
Build predictive models
Develop AI-powered user interfaces
Translate data science into real-world healthcare applications