The Automators during the hackathon
The hackathon started effectively at 1 pm, and we had until 1 pm the following day. The first hour we had the nerves of the beginning: where to start? What do we do? Everyone wanted to do something but we were not sure how to begin and how to combine efforts. A group of techies and a group of agriculture experts needed to find some sort of common ground to work together. Eventually, we agreed on some ideas and everyone started working.
The total number of input parameters that we could give to the simulator was nearing 1000, where each parameter could have different values within a certain “reasonable” range that the horticulture experts could define. If we assume each value could have around 30 different “reasonable” values, we get up to 30.000 different possibilities to test. If the simulator took 15 seconds to respond as it did: we needed 125 hours, or over 5 days to test them all. But we had only 24 hours.
These input parameters were mainly setpoints for the climate computer. Temperature, CO2, lighting, screens, irrigation. The ag experts in the team helped us determine some reasonable bounds, and based on that we had to explore and get results. We couldn’t of course test all the possibilities in the given time. Otherwise, it would have been an easy problem. And we could only make one call at a time to the simulator. Each time the simulator would give us a result: what was our net profit?
We did start brute-forcing randomly at first, but soon we wrote a better exploration algorithm, giving it a “reasonable” starting point for inputs, looking at the result and keeping the new one if it was better. Our data scientist called this the “Monte Carlo-ish” approach.
In the meantime, we gave the experts an easy to use tool through which they could also experiment with other parameters, calling the simulator and learning from the results. They tried to answer questions like “if we give as much light as possible do we get the most production?”, or “if we give more nutrition to the plants, do we get tastier tomatoes?” and how does all this impact the net profit?.