Show HN: We open-sourced our compost monitoring tech

For Monty’s system, we use sensors from Bosch and Sensirion. During our initial prototyping phase, we tested around 20 different types of sensors and found they had the most workable results across a range of composting environments.

Feel free to share more about your project ideas— happy to dive deeper if it helps!

To dive into the utility of the sensor readings-- The main gas we monitor is Total Volatile Organic Compounds (TVOCs), which act as a general proxy for decomposition activity. Combined with temperature data, this gives a strong indication of whether the activity is aerobic (a healthy compost pile) or anaerobic (not ideal and potentially smelly!). For example, a spike in TVOCs with decreasing oxygen availability often flags anaerobic conditions.

In terms of air pressure, this is used as part of our pile turn events detection in our companion app Monty Mobile. The app also analyses other data to assess how changes in conditions (e.g., moisture levels, turning frequency) affect decomposition. For most users, though, the general proxy is plenty— by identifying when a pile is “active” or “stalled,” they can tweak their process (e.g., adding browns, adjusting moisture, or aerating).

Compost is incredibly diverse, and the results will vary depending on the setup (tumblers, bins, worm farms) and inputs (manure, food scraps, garden waste). That said, 24/7 data from our system helps streamline the behaviour-change process. Rather than relying on a “try-wait-try-again” approach, users get immediate feedback, which can be a game-changer for both beginners and seasoned composters.

As for me, Monty has been a massive learning tool. Using the Monty Mobile app has personally helped me engage more with my compost pile and remember to add feedstock to adjust the pile when needed. It definitely makes me feel more in tune with what’s going on!

I hope this clarifies things! Happy to chat more :)

Great question— thanks for asking!

Verifying the metabolic processes in composting is a bit of a mix between understanding composting fundamentals and interpreting the data we collect. The processes are highly dependent on factors like feedstock type and volume. For example, a sudden spike in temperature might be due to an addition of nitrogen-rich materials or a recent turning of the pile—both of which can accelerate microbial activity.

While our sensors provide 24/7 data on temperature, gas composition, and more, there are always factors we can’t directly see or control for, like the exact distribution of materials within the pile. That’s where a bit of interpretation comes in: matching what the data is telling us with the fundamentals of composting.

By combining real-time monitoring with an understanding of what’s happening in the pile, users can make informed decisions to keep their composting process on track. It’s not an exact science, but the extra data helps a lot!