#MVP Hardware Needs
Using my three tier concept of a MVP, I want to speculate about the level 2, and particularly the sensors. I am assuming either a generic bus tub, or a custom reservoir; but I think the growing environment does not need to be standardized at this point, neither does the enclosure; though we should offer one or more suggestions. While we may have several lighting options, as long as we know the PAR equivalency of them, we don’t have to have one specification.
Without CO2 regulation, a CO2 sensor does not seem to add much value (assume normal atmosphere of 399 ppm), though an enclosure will have some variation (negligable? - good trial experiment!). If you have an air pump running in the water, the O2 is also probably not a concern (assume 100% saturation). Follow a nutrient change-out schedule and you can avoid the dosers, I think we can also avoid the water chiller. That basically gets rid of the expensive parts, and still gives a lot that can be experimented with.
The critical standardization seems to be sensors, the question is what is the minimal sensor set, and what are their priorities (now we can get a real debate raging!!!). I am assuming a RaspberryPi (Zero?) and an arduino, all UI is done through a web interface and another computer, no screen for the MVP.
- I think the minimum is a temperature/humidity sensor (SI7021?)
- With an enclosure, there will be a need for air circulation and ventilation. PC fans can probably do the job, and run off the arduino 5V. This will require some programming for fan control (though the circulation fan could always be on). I don’t think there is a need to monitor air circulation, and the cfm (cubic feet per minute) rating of the fan can get us in the ball park.
- I am tempted to say a LUX meter should be the next addition, but other than being simple and cheap; I am not sure it adds much if we know the light output (it should always give the same reading).
@Webb.Peter has argued that a camera should be a high priority. I am beginning to be convinced that he is right. 1) It has a high social value, the ability to post pictures on SnapChat, Twitter, Facebook, etc; and the ability to ‘check up’ on the plants remotely from a phone (with the right UI). There is a high value to keep the excitement level up. 2) Images have the potential to provide a lot of data (with the right software) and avoid the need for so much manual phenotype data entry. With a timestamp, you can tell when the plants were started (or at least transplanted), harvested (no more plants) and other metrics like size and possibly health. There is a lot that can be done here, and the possibility of going back later and extracting new information with new logic. 3) While not the cheapest sensor, the Pi camera is a great camera for the cost ($30). This is an area where I don’t trust my judgment and would like other’s opinions. At my age I am not as social media aware as the younger generation, and I don’t know what @Caleb has up his sleeve for AI work with images.
How smart could we get with using images for data entry? For pH, I am thinking of a standard color card (with a QR code to indicate this is a pH reading?), use General Hydroponic’s pH kit, mix up a sample and image it in front of the card. Hit a button to take the pH image, and the logic could identify this as a pH reading. Are there other colorimetric readings that would be useful?
From a hardware perspective, I think this basically covers it - with one more piece. I think it would be highly valuable for OpenAg to have an Arduino (or Pi) shield and cables to simplify hooking up sensors. It wouldn’t need to be much more than some I2C plugs, and plugs for the fans. There should be the potential for a lot of expansion (other sensors), in which case this may be the same board as the PFC (if the cost is right). I definitely don’t think we should expect people to wire up and maintain breadboards (though that is what I am currently using), or learn to do much soldering. If OpenAg offered a board for sale (and possibly the sensors), it would go a long way toward the MVP.
Software is also an issue. Does this need the full PFC stack, or could something more stripped down work (cloud data storage?). How frequently do sensor readings need to be taken (cpu demand)? Once an hour? Maybe a bit more frequently, and the camera can detect when the lights go on and off (no need for a LUX sensor). Plants are constantly changing, but not by that much. This may be a three ‘node’ software architecture. Something light on the MVP end (just collect sensor data), a light weight UI for checking the MVP, and some robust data storage, analytics, charting and display on a web server/UI. We probably need to think software through from a MVP perspective, what do we need to get started, and what can be added over time.