In our latest article about the OpenWeather Challenge, we highlight one of this year’s finalists, Daniel Dake, whose work connects environmental data with personal health. In a recent discussion with the Weather Foundation team, Daniel shared his journey from Ghana to the United States and explained how he leverages technology to create meaningful social impact.
A Journey from Hardware to AI
Daniel’s participation in the OpenWeather Challenge was sparked by Trestle Academy, an IT training organization in Ghana. Despite a heavy academic workload, Daniel felt compelled to participate, seeing the challenge as a unique opportunity to build an accessible solution that could directly influence well-being.
Project Snapshot: Weather-Driven Health Risk Dashboard
Daniel’s entry focuses on the intersection of weather and wellness. He developed the Weather-Driven Health Risk Dashboard, a tool designed to estimate daily personal health risks. The system integrates real-time data from OpenWeather with lightweight machine learning to analyze environmental hazards.
The dashboard calculates risks for specific conditions such as asthma, heat stress, and dehydration. It uses a local AI model to translate complex meteorological data into plain language, offering users clear safety recommendations based on their profiles. The project prioritizes privacy by processing data offline, ensuring that sensitive health information remains secure.
Insights from the Development Process
Daniel made several key discoveries while working with weather data. He discovered that the correlation between specific weather patterns and health risks is stronger and more predictable than many realize. His testing revealed distinct relationships between environmental variables and personal hazards.
Daniel outlined the following key observations from his research:
- Heat index and humidity levels are the primary drivers for both heat-stress and dehydration risks.
- Particulate matter and ozone levels are the dominant factors when calculating asthma risks.
- Dehydration modeling is a critical addition for protecting vulnerable populations, especially older adults.
- AI summaries effectively bridge the gap between raw scientific data and actionable personal health advice.
A Vision for Future Collaboration
Even though Daniel was not among this year’s winners, he is still enthusiastic about future collaboration using OpenWeather Data to expand the rach of his work, helping universities and other organisations work together to build early warning systems that are accessible to everyone.
