UncleCorn Autonomous IoT Corn Vending

its a mockup of our project, it will take few more weeks to finish real one

About the Project

This project started with a small, almost forgettable moment.

I was standing on the side of a busy road, watching an old corn vendor struggle. Boiling water over an unstable flame. Handling cash with wet hands. Guessing salt, guessing time, guessing demand. By nightfall, unsold corn was waste. By morning, the same cycle repeated. No data. No leverage. Only physical exhaustion.

That moment exposed a pattern I couldn’t unsee: essential street food feeds millions, yet the system behind it is fragile, unscalable, and punishing to the people running it.

That is where UncleCorn began.

Inspiration

Corn vending is simple on the surface, but operationally chaotic. Hygiene depends on the vendor. Consistency depends on experience. Profit depends on luck. I wanted to remove chance from the equation. Not by replacing the vendor, but by replacing uncertainty with systems.

Robotics isn’t always about humanoids or factories. Sometimes it’s about applying control logic to everyday survival workflows.

What I Built

UncleCorn is an autonomous IoT-enabled corn vending machine designed as a dispatchable unit.

The system automates:

Water temperature control for consistent boiling
Timed cooking cycles based on batch size
Automated seasoning dispensing
Portion-controlled vending
Sensor-based inventory tracking
Remote monitoring via IoT dashboard

At its core, it treats street food like an industrial process , measured, repeatable, and improvable.

How I Built It

I broke the problem into three layers:

Physical layer
Heating elements, food-safe containers, dispensing mechanisms, temperature and level sensors.
Control layer
Microcontroller logic handling boil cycles, safety cutoffs, and sequencing: [ T_{boil} \rightarrow \text{hold} \rightarrow \text{dispense} ]
Data layer
IoT telemetry for usage frequency, stock depletion, and fault detection so the machine reports its state instead of silently failing.

No unnecessary complexity. Only what improves reliability and scalability.

Challenges Faced

The hardest challenge wasn’t technical, it was restraint.

It was tempting to over-engineer. Add screens. Add features. Add intelligence where none was needed. I had to keep asking one question: Does this reduce human effort or increase system reliability?

Hardware tolerance, food safety constraints, and power stability were constant constraints. Every decision had physical consequences. Software mistakes can be patched. Hardware mistakes sit there, judging you.