That's a great question. Actually, one of the sounds that are pretty close to a chainsaw are mosquitos that are circling around our microphones due to the Doppler effect. We found ways of dealing with signals that are close to chainsaws by aggregating multiple models and also a time-based analysis. The system can draw causal/correlative conclusions such as a vehicle is usually present before a chainsaw. If there's no vehicle, the likelihood of a chainsaw goes down and the chainsaw model must be highly confident before we sound an alert.
Thanks! We are a relatively small engineering team and we were mainly focused on improving our system. This took a lot of effort and time, we just haven't had a chance yet to think about open sourcing or blogging. Our days were focused on coding. If there's interest in blog posts, I could write up some of our technology. Just let me know whether there's an interest and what you'd like to know.