The goal of this project is to finalise the development of a data-driven fermentation management solution i.e. non-invasive Internet of Things solution to monitor and control fermentation in the beer industry.

Currently in Europe, 9 out of 10 microbreweries do not have access to the right tools to monitor and control fermentation. The breweries end up using analogue solutions if any, which require time-consuming manual sampling and include weak data flows. Lack of appropriate quality control results in low and inconsistent product quality, production inefficiencies and large amounts of beer and CO2 spillage.

As of today, in Europe there are over 11,000 microbreweries, so such a solution is very much needed in the industry. Fermentation processing in microbreweries is highly complex due to the involvement of various raw materials, different yeast strains, numerous quality parameters, biased factors and interventions throughout.

Zymoscope will start this project together with Flying Couch Brewery in Denmark, where various beer fermentation processes will be monitored to collect sufficient amounts of data and, through that, improve accuracy and reproducibility while ensuring the scalability of the solution.

Final report summary
The solution consists of a hardware part and a software part. The hardware part is mounted on the fermentation tank and tracks key fermentation parameters. The software part processes the fermentation data from the sensor device and calculates additional key parameters.

Based on early estimates, validated through interviews with brewers, brewery capacities may increase by 14% through the use of the Zymoscope solution. 8% of this increase comes from shaving one day off the fermentation time. Due to the continuous monitoring, the fermentation process can be stopped the second the alcohol and CO2 levels reach the right plateau. With traditional sampling methods, several samples are necessary to confirm that fermentation has stopped. The additional 6% improvement in efficiency is realised through early detection of bad batches, compared to sampling techniques which take several days.

The Zymoscope solution enables resource efficiency through three avenues:

1.Reuse of yeast for additional batches, since the algorithm will be trained to detect how many times the yeast can be reused
2.Fewer bad batches as real-time monitoring gives the brewer an opportunity to save bad batches and troubleshoot slow fermentation
3.Less waste, since no samples are needed.

Several breweries have validated the solution, either in their production environment or in a prototype setup.

The project has enabled Zymoscope to acquire user feedback, proceed with developments within UX/UI, test various mockups with Flying Couch and other brewers, finalise designs and proceed with the development of a user-friendly app.