- The coolest and most challenging: pH, EC, and flow rate
The hardest part has been running everything on battery while maintaining accuracy and using LTE (2–4G) and not common LPWAN options like LoRa. I'm primarily a software guy, so the learning curve has been huge.
It's a SaaS + IoT + Plant Biology knowledge baked into one package. We are figuring things out on the fly as well (here's a link to one of the products https://www.hexafarms.com/main/hexaos). The aim is that the entire operations should be reduced to manual labor of handling the plants (and our software will inform you about that as well). Vertical indoor farming has been always close to my heart but at this point we address the wider space of Controlled Environment Agriculture (CEA) in general.
> How are you different from “VC-backed vertical indoor farming companies”?
Yikes! We are also going to be VC-backed soon. Went through Techstars recently. Hopefully, I'd have the humility to accept and not makes claims that go against the fundamental principles of physics, biology, and economics. Sorry but this is the best answer I could give.
We built a company around this very problem- indoor farming (including vertical indoor farming) is pretty complex and by default it's energy hungry. In theory, indoor farming is very efficient for commercial food production though. I thought we could be the company that does all the plant biology, automation complexity magic for growers, and growers just do seedling and harvesting in a super basic mechanical setup.
We are working with growers in EU, and they are all actually profitable growing normal veggies (lettuce, kale, etc.) as usual. But whenever we talked to some of the fancy VC-backed vertical indoor farming companies, they would usually not entertain us and would always claim that they were going to build everything by themselves. Almost always, the leadership in these companies was the type that didn't know anything about plants, software, status quo of AI, etc.
I didn't want to confess, but yes you're right. Elixir (or the willingness to learn Elixir) is a great filter for me to find the right people. Again, this is my purely subjective opinion and might as well be true for other languages as well.
I know-- I was scared like hell. But after the first week and multiple staging releases in less than 10 days, I was on top of it. Yes, hiring is real challenge and am facing it already. However, if I, even as a startup, reach the salary threshold, then hiring is not a problem. I'd say I've yet not found a case where I couldn't find a library for my use case.
I second this. I would say that I am pretty advanced with Python (and Django) and same with JavaScript (Vue and Nuxt) and have written applications that got used by multiple users. I saw a sharp rise in my productivity when I knew enough about the frameworks. But Elixir + PhoenixLiveView + Tailwind has been life changing.
I learned Elixir for the sake of the joy of learning a new programming language and I kept playing with it for few random days over 5-6 months. Finally, I took the leap of faith and for our startup I started the switch to Elixir + LiveView with minimal JavaScript hooks and I feel a weird bliss that we are two engineer FTEs and I can add features on a daily basis. Why that's the case, I still haven't ruminated myself, but my guess is 1. I have gotten older, 2. Elixir is beautiful and productive by design-- pattern matching, everything is a process (so the dimensionality of time is not an issue at all) and the code is kind of a right balance of simplicity and complexity, and in my opinionated view, there is "one" right way of doing things. 3. Standard tooling (mix, ExUnit). They have enabled us to write really maintainable code and for our next hires, we are willing to pay for them to learn Elixir than switching to other languages. Of course this is only for true for our web app which is actually a weird beast that interfaces farms, sensors, algorithms, and humans.
Quite few I had (assuming OPs question to be broad enough)-
1. Reading Malcolm X's autobiography _The Autobiography of Malcolm X_ in college. It transformed me such that within that one week of reading it, I developed (given my low standards) the strongest sense of orderliness in my life. Additionally, I decided for myself 'to straighten myself up' for this life.
2. Reading Dostoevsky's _Brothers Karamazov_. My 'inner' transformation (at the age of around 20.5) was so immense that it was also apparent from the outside. My transformation was 'not to be surprised by bad/evil' and seeing good in everything.
3. In programming/ computer science/ functional programming/ mathematics (I still don't fully get LISP, Haskell et. al. like other people here) but there are encounters in the field of lambda calculus, computation, cryptography that have left me totally transformed. Too many to elaborate.
Funny story: I was rejected by YC last batch. But I get it- I thought they look for traction and what not, so I rather made the pitch video on a very specific aspect of Hexafarms- which is monitoring, since some people were willing to check it out. No doubt YC would reject it. On the other hand, Thiel Foundation reached out to me, but they had some drop out thing and what not which I was not able to fullfil (and after a while they also stopped reaching out too).
I actually graduated from college this year; and for personal reasons I've had to change countries; now I'm in another Master's program... ready to drop out anytime. The whole project has been dead for months once in a while! I'm more trying to leverage ML for optimizing things. I guess that's what modern farming is missing (not ML per se, but optimization).
I'm trying to raise some investment (or in the worst case bootstrap and risk everything in the next few months), then I will go crazy with the idea.
You'll have to buy my words- but taste wise (based on my surveys too) it's the 'best' they have had (mostly city dwellers I'm talking about).
Yes, you don't really need sunlight whatsoever. I was myself shocked until I recalled high school biology concept of genotype and phenotype i.e. the genetic structure that manifests itself given the right physical conditions (at least of plants.) As for the plants' nutrients, here's a classic- Teaming with Nutrients: The Organic Gardener's Guide to Optimizing Plant Nutrition, by Lowenfels. I was amazed to find how complex, yet simple plants are.
>It would be awesome if people living far from traditional agricultural areas could access fresh greens without insane transportation costs (both financial and environmental)
That's what actually got me started. A head of lettuce on average 1200 miles (https://ucanr.edu/datastoreFiles/608-319.pdf) and it is so disconnected from the site of consumption.
My vision is to have distributed farms (as opposed to conventional wisdom, i have found that smaller indoor farms will be more profitable) every eight blocks or so.
Not really- It's quite manual (as of now). I had to change my country almost three times since I started; so I'm rather focussing more on data, and training algorithms part to figure out the right parameters (and the farm is a just a testbed). One example would be to have a $5 camera for measuring growth than buying a $100 3D what not camera.
I'm growing the freshest lettuce, iron-rich kale, and a lot of other leafy greens!
While in college (CS & Math), I got heavily interested in growing food in the most efficient and healthiest way possible. I was a dreamer when I started so I thought more of how to grow 'earthly' produce on Mars, but then I realized that my own planet Earth is so massively underserved.
It's basically like this- I mastered growing leafy greens in indoor closed environmenet, then I tried to cover all the major physical and biological markers, then I try to optimize the most optimal levels of 5-6 variables (currently) that I can fully control and may produce the best phenotype- CO2, O2, Light, Nitrate, P, K. These parameters have their own sub definitions.
So far I have had great results. I am trying to raise investment so I can finally make it a reality. Check the numbers here: hexafarms.com (no fluff)
- CO2. Side note: I was surprised to find that most (all?) CO2 sensors used in closed plant production setups are not meant to operate below 400 ppm.
- Air temperature, pressure, relative humidity
- Photosynthetically Active Radiation (PAR)
- Addons like: wind speed, wind direction, soil moisture and Electrical Conductivity (EC)
- The coolest and most challenging: pH, EC, and flow rate
The hardest part has been running everything on battery while maintaining accuracy and using LTE (2–4G) and not common LPWAN options like LoRa. I'm primarily a software guy, so the learning curve has been huge.