Bloombot

Bloombot's dashboard
Add plants section
Setting thresholds section
Monitoring plants section
AI climate forecasting

Inspiration

BloomBot was inspired by a simple problem: farmers have access to environmental data, but raw numbers do not always tell them what action to take. We wanted to turn climate data into understandable, plant-specific insights.

How We Built It

We upgraded BloomBot into a Climate Intelligence platform using PHP, MySQL, JavaScript, Tailwind CSS, and Chart.js. We integrated live environmental observations from the JKUAT Conduit monitoring stations, including temperature, humidity, wind, rainfall, and heat-related measurements.

The system combines these observations with plant location and thresholds to generate climate health, risk levels, alerts, irrigation insights, and explanations of what is changing and why.

What We Learned

We learned that climate intelligence is more than displaying data. The challenge is transforming multiple environmental measurements into information that people can actually understand and use.

We also learned about working with live data, API integration, location-aware monitoring, dashboard design, and building intelligence on top of an existing application.

Challenges

Our biggest challenges were working with real-world environmental data and integrating new intelligence into our existing PHP system within a limited timeframe. We also had to account for the fact that monitoring stations may not be located directly at a plant.

These challenges helped us build BloomBot with greater focus on context, transparency, and practical decision-making.