CLIMATE ACTION ASSISTANT

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  Location Selection

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  Profile Selection

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  Language Selection

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  Dashboard

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  Actions Page

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  Risks Page

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  Community Page

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  Settings Page

Inspiration

Millions of people daily—especially those depending on weather conditions for farming, transportation, domestic chores, and small businesses—are affected by climate change. Weather applications give projections, but they seldom address the fundamental issue: what should consumers do with this knowledge? We found this discrepancy and chose to create something more practical than predictions. We set out to turn weather information into useful actions that would enable people to maximize risk reduction, increase productivity, and enable better decision-making. Climate Action Assistant resulted from this.

What it does

An artificial intelligence-powered tool called Climate Action Assistant turns weather forecasts into practical suggestions. It explains what the weather means for every user instead of just presenting data like temperature, precipitation, humidity, wind speed, or UV levels. Users choose a category—Farmer, Student, Household, Small Business Owner, or Community Leader—and get individualized direction.

Important qualities are: Climate opportunity score Recommendations grounded on actions Flood and danger warnings Gardening and planting notes Energy-reducing ideas Methods of rainwater collection Solar energy prospects Community security warnings

Using weather data, the aim is to enable consumers to make better daily choices.

How we built it

Using Replit AI during an artificial intelligence hackathon, we developed Climate Action Assistant. First we set out to understand the issue: Though people watch weather predictions, they may not always know how to respond on them. Then we created the user flow based on this concept. The frontend, backend architecture, and main capabilities were all generated with Replit AI's help. Prompt engineering was used by us to help the AI create dashboards, recommendations, and weather integration. Focusing on ideation, testing, and making sure the product was realistic and useful was our team — Tope, Moyo, and Gbemi.

Challenges we ran into

We had to concentrate on actual value rather than creating only another weather app. We also developed several suggestions for several user groups, which called for a lot of thought. At last, inside the constrained hackathon time, we found a balance between speed and quality.

Accomplishments that we're proud of

Converting meteorological information into practical knowledge Creating a Climate Opportunity Score Building user-specific dashboards raising awareness of climate change Designing an artificial intelligence (AI) answer grounded in actual reality

What we learned

AI is most effective when addressing actual issues, not just presenting data. We also developed knowledge of teamwork, prompt engineering, and user-focused system development.

What's next for CLIMATE ACTION ASSISTANT

Future growth across Africa, we want to include SMS alarms, improved AI recommendations, local language support, community reporting, and flood prediction developments. We want to empower people to properly apply weather knowledge, not only to grasp it.

Built With

• open-ai
• open-ai-api
• replit