From Buckets to Bytes
Like many students, I discovered homebrewing at university—not out of a desire for artisanal craft beer, but as a way to stretch my tight budget while having some fun. I remember the excitement of picking up my first kit: a simple plastic bucket, a packet of sugar, and a set of vague instructions. With nothing but enthusiasm and YouTube tutorials, I dived into the process. The results? Questionable at best, but undeniably rewarding.
Looking back, what started as a basic setup of a fermentation bucket and a pressure barrel became more than just an attempt to save money. It was my first proper DIY project. Now, with a few more years of life and IT experience under my belt, I’m revisiting this hobby — but this time, I’m bringing a Raspberry Pi along for the ride.
My Original Setup
My university setup was as simple as it gets.
- A plastic 25L fermentation bucket
- An airlock to release CO2 during fermentation
- Sugar and malt extract packs
- A basic hydrometer
- A plastic pressure barrel for dispensing
The process was all manual: measure by eye, record temperatures in a notebook, and hope for the best. Temperature control consisted of moving the bucket closer to or further from my uni room’s radiator.
Fast forward to today, and the opportunities to modernize homebrewing is endless; embracing automation, data collection, artificial intelligence and remote monitoring.
My New Tech Stack:
Components:
- Arduino: Hardware control (temperature sensors, heating elements, pumps)
- Raspberry Pi: The brains of the system, running BrewPi and managing local control and data logging
- BrewPi: Open-source brewing controller software for temperature regulation and fermentation management
- AWS SageMaker: Cloud-hosted machine learning platform providing AI-powered analysis, predictions, and brewing recommendations
Core Features:
- Real-time temperature control via Arduino
- BrewPi web dashboard for monitoring and manual adjustments
- Raspberry Pi for data storage and remote access
- AWS SageMaker for AI-driven batch predictions and pattern recognition
- Remote alerts and historical batch records
Ai & IoT Integration
AWS SageMaker will:
- Analyse fermentation data (temperature trends, duration, batch history)
- Predict likely ABV, fermentation duration, and risk of stalled fermentation
- Recommend temperature adjustments or flag anomalies
- Send results back to Raspberry Pi for display within the BrewPi dashboard or via notifications
Homebrewing has always been about experimentation and learning in my eyes. By integrating IoT and AI, I aim to improve consistency across batches by gaining meaningful insights from my brewing data. I will keep my site updated with developments as and when they occur if you are interested in following along!
+-----------------+ +------------------+ +-----------------+
| Temperature | | Heating Element | | Pump / Valve |
| Sensor(s) | | / Cooler | | (Optional) |
+--------+--------+ +---------+--------+ +--------+--------+
| | |
| | |
+----v-----+ +-----v------+ |
| Arduino |<------------>| BrewPi |<------------------+
+----+-----+ Serial | (Raspberry | GPIO / USB
| Comm | Pi) |
| +-----+------+
| |
| +--------------------+----------------+
| | Local Web Interface (Pi) |
| +--------------------+----------------+
| |
| Data Sync
| |
+----v------+ +-----------v-----------+
| Local Data |<----->| AWS SageMaker Model |
| Logs | | Predictions & AI |
+------------+ +---------------------+