- Focus
- Readable monitoring and control
- System
- Sensors, Azure, MQTT
- Outcome
- End-to-end field workflow
Context
CropCare came from a simple observation: a lot of smart-agriculture demos prove the hardware works, but stop short of showing a software workflow that someone could actually trust day to day.
The project was meant to connect field signals, cloud automation, and a readable operator experience inside one end-to-end story.
Build
I used an Azure-backed MQTT pipeline to move between sensing and response, so the system could both observe conditions and react without feeling like a disconnected hardware demo.
The interface work focused on making monitoring and control legible, which helped the project read as a product prototype instead of a bundle of technical parts.
Takeaways
The final prototype demonstrated reliable two-way communication between field data and cloud-side actions, which was the most important proof point for the concept.
It also gave me a concise way to explain how embedded constraints, backend integration, and user-facing control design fit together.