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So Gretchen and Neta, no strangers to the Vertical Farming Podcast. Thank you
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so much to both of you for joining. I know I've been in conversations
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with Neta about an opportunity to come back on the show, and she mentioned some
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work you guys were doing together. So just to kick things off, Neta, you want
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to kind of talk through what prompted the desire to come back
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on and share what you've been working on? Yeah, absolutely. Thanks again for having us
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on the show. It's good to always chat with you again, Harry. It's always,
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we love chatting with you because it's this organic conversation where you
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really highlight what's going on in the industry. And what really prompted me to come
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back and have a conversation was to shine some light
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on a project that we worked with ERI. Gretchen
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brought us into a project which was called the CalNEX Project, which was
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really taking a look at the energy consumption that's being used in the
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greenhouse on operations and really understanding
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does adding more environmental monitoring and controls actually
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make a difference from an energy usage perspective? This was
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the first study, from what Gretchen described to me, that was really
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being looked at from a very scientific perspective. And having had a science background,
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we were really excited to be a part of this project, which is really looking
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at things side by side, kind of what we call the smart room
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versus a smarter room over a long time period. So really exciting to
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be back on this show to talk to you guys about what the findings were
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and what Gretchen's team and was able to learn from this project.
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Thanks for that context. And Gretchen, I think what would be helpful for the viewers
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is to kind of share how long you've been involved in horticultural lighting research
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as some context leading into this collaboration. Yeah,
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sure. So in 2021, I was on a team
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that worked with one of the largest utilities in North America, Commonwealth
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Edison, that serves like Chicago and a lot of areas in
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Illinois. To explore what they called the opportunities in controlled environment
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agriculture. And so at that time, I started this theme of looking into
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and uncovering the benefits of LED lighting and automating those
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systems. And not just the energy benefits. At that time, I was actually looking at
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what the utilities call non-energy benefits. So I think that's what growers
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often care about more, right? Is, yeah, energy savings, but also what
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else? What happens to the plants? What happens to the the labor benefits and other
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things like that. So then in 2023, I took on the part-time role of being
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executive director of GLAZE, the Greenhouse Lighting and Systems
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Engineering Consortium at Cornell University. And I got to collaborate with amazing
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scientists, still get to collaborate with amazing scientists at Cornell
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University, Rutgers University, and Rensselaer Polytechnic Institute.
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And at that time, I was helping them complete this NYSERDA-funded
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greenhouse lighting research. Which took a look at not just the beginning
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of LED lighting adoption, but also the adoption of
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dynamic lighting controls. And that's where we're going as I get to the
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point of where I started to work with Netta. So in 2023,
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you know, I had been running into Netta in the industry quite a bit, and
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we collaborated a bit when I was at Resource Innovation Institute. But in
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2023, now at Energy Resources Integration, I applied for funding
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like we all try to do. We try to get some funding from someone else
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to do something cool. So I applied for funding from a California utility program
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called CalNEX. And what they do is they explore energy efficiency
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technologies and vet them for inclusion in rebate
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programs, right? So how can we get new tech to get money so
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that growers can adopt it, so that any business can adopt it? So from
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2023 to 2025, Neta and I collaborated on the Smart Controls
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Project, where we explored how these dynamic
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controls for lighting, climate control, as well as energy monitoring, like Netta mentioned,
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really prove out the energy benefits so the utilities would give out rebates,
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but also prove out the benefits for the businesses so that they would want to
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do it too. So we completed 4 field demonstrations at 3 different
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farms in California. And, you know, this year we're really running
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around celebrating the results, which is that it proves that these
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will beneficial and that utilities should provide rebates. And hopefully
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the wave will just be beginning now of rebate programs
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offering more for controls, and more research and education
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about this will continue to see growers adopt it more. So that's my history for
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the past 5 years in this field, and I really loved the past few years
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being able to collaborate with NETA. Sounds like you guys had a— it's like a
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match made in heaven in terms of what NETA's been working on Neda, what made
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Microclimates a good fit to support this project with CalNext?
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Yeah, I'd say the biggest thing was probably that we are
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unique in the sense that we're not trying to replace any environmental
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control system. Our job is to complement what's already
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there. And the projects that— the locations that
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Gretchen mentioned, every site had something different. One of them had
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a Ritter control system, a very robust, great company. Another
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one had a Priva. Another one didn't really have much
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automation. So, our job wasn't to go in there and just say, rip everything out
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for this control study and start over because we want to collect the
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data. It was really to take a look at what do you currently have, how
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can we complement that with adding more environmental insight,
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environmental visibility to that operation, and is there a way that we can integrate
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what you currently have? Will that control system allow you to integrate
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And what does that look like? So it really just sort of demonstrated how additional
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environmental monitoring and not ripping and replacing can really bring a lot
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of value. And what did that experience teach you about what is
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being collected now? Was there anything surprising when you went in?
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Yeah, I'd say the biggest surprise wasn't necessarily that they
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weren't collecting data because they were all collecting data. It was really
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the biggest surprise and biggest lesson was that they didn't have enough environmental
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visibility. So, what I mean by that is that a lot of these
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operations had maybe one temperature humidity sensor hanging
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in the middle of the room representing the entire greenhouse or a section of the
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greenhouse. And your control system is only as
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good as the information is taken in, like the input, right? So, it really shined
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a light on the fact that they didn't have enough environmental
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visibility. And the perfect example that I love referring to
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is Floricultura, one of the sites.
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Their crop is an orchid. So they're growing orchids, very
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finicky plant, as we all know. Yeah, very finicky. But they really just didn't really
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understand the environmental temperature, humidity
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environment that the crop was actually experiencing at a root zone
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level, below the root, above the crop, above
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their screens. So that was really important. And we have a grower there
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that's very data-driven, data-rich. He really
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understands orchids. He's probably world-renowned for his understanding of orchids.
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And having that insight was so valuable to him. And Gretchen
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can talk a little bit more about what the outcome of that study was, but
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that was a kind of aha moment that we had, was, yes, they're collecting
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data, but they don't have enough crop environmental
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visibility. And then the question that really came for us at the end was,
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if they're not collecting enough data as it is, How's this world going
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to prepare them for AI, which we can talk about later? But that really got
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us thinking from an AI perspective as well. So yeah, she's teed that
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up for you perfectly, Gretchen, the experience with that. And I'm also curious how you
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pull in all these learnings that you have from all these other locations
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you've been at, all this other research you've been doing on smart controls. And I'm
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curious what your perspective was specifically with that company that Neda
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mentioned. And then what comes to mind for me is like, Does the then grower
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have to think about, oh, I need more sensors now to capture all these different
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locations and all these different places? And I'm sure there's concerns there as well. Yeah,
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I think the— I'll reiterate Neta's surprising moment as
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well of realizing that the field demonstrations are
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using pretty static controls or pretty basic
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controls. So that presented an opportunity for us. I
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think that in the floricultura example, They have a sophisticated
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control system, but what they don't have is a lot of feedback loops
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telling them what's happening at the grower level. The system knows, and it
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adjusts the screens, and it might adjust the lighting, but they aren't perhaps getting
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the info where they can find fault detection. Another site at the
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lettuce greenhouse, the load shape of the lighting circuit looked pretty much the same
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every day, even as the seasons were changing. And so my job as an engineer
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when I'm validating a technology for a utility is, what's the
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baseline? What would they do if we didn't affect anything, if we didn't
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offer a rebate? And so for me, this helped us prove
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that scheduling lighting with time clocks is an industry standard
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practice. And so utility energy efficiency programs
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could help growers save even more energy by using sensor-based controls. And
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instead of just using schedules, they could use sensors to control their lights. With
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floriculture, they're not using lights as much, but with lettuce, the lighting
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was much more of an important thing. So with mushrooms, one of our other
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field demonstrations, the humidity and the climate values were much
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more important. So it's sometimes what we found was surprising
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because it was like, there's a great energy savings opportunity. And then sometimes what we
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found was more surprising of like, wow, there's a real big like information
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gap here that Netta's system can help fill by just providing
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things like trends. Because, you know, I'm used to commercial buildings
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where you can go back, open up the computer log, see months of
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trends, see what all the office building temperatures were in all the different
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rooms. But some growers we found, all they knew from a
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climate level was something that was at a very, like Netta said, one sensor
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in one place. And then all they knew from an energy level was the utility
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bill. For the whole greenhouse. So, Nada was helping us piece apart,
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okay, well, this is actually how much is going to lighting, and this is what
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the lighting's doing. This is how much is going to fans, and pumps, and all
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the other stuff that sometimes is more energy-consuming for a different type of grower that
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doesn't use lights. So, Nada, I imagine a lot of this information
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you've been learning in your interactions with your clients, and the folks you've been
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working with, and all the facilities you've been able to have access to. But, how
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much of this was a learning for you, and because of this partnership, because of
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the in-depth visibility you had to what was there already,
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and maybe some preconceived notions about what people think growers are
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measuring versus what's actually happening in these facilities? It was
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quite a surprise. I think I had the vision. I assumed that
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they were collecting a lot of data, and then we, I think, also made some
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assumptions that they understood a little bit about their energy consumption, at least
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maybe like— because we, we've heard this over and over and over again the past,
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you know, 10 years— overhead costs are too high?
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What happened to the company that just started and they spent millions and raised
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millions, hundreds of million dollars to build this beautiful vertical farm? And why
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did they go out of business? Over and over again, the theme that we have
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heard is that overhead costs, overhead costs. And we know that 70%
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of their energy consumption is related to their HVAC
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systems and their lighting system. So I think I had made the assumption that they
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must understand something about their energy consumption. And even the companies
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that had a whole sustainability team. We started out with one of them that had
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a whole sustainability team dedicated to it. They really cared
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about this topic, and they knew all about it, but they really
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weren't collecting energy data at a circuit level,
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at, let's say, a pump level, at a lighting
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level. So, it was an aha moment of they actually don't
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have visibility into that data, into how much energy is
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being used. And if you don't have that visibility, How are you going to make
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small changes so that you can reduce that overhead cost? Is that
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common, Gretchen, from what you've seen? Obviously, you've done a lot of this research a
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lot. And I'm also curious if there's a difference between controls that
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need to be monitored on the greenhouse side versus pure vertical
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farms, and if you have enough data to kind of back that up.
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Yeah, I appreciate you bringing up that there's maybe different baselines for
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greenhouses and vertical farms. And if you check out the results of my study
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with Netta, If you look at what we did was we created a tiered
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hierarchy of control sophistication levels. So level 0 is
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basic. Level 0 is manual. Level 1
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is when you start to have some basic controls like a
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timer. And then when you start going to level 2, that's when we start to
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have some sorts of an automation system going on, but they're not
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talking to each other. And then as you go up the levels, you start to
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have actual system integration. And what we tried to do with the study was for
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every system, lighting, HVAC, and irrigation, what
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level are they? So we did surveys, we did interviews, site visits,
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and field demonstrations. And when you take a look at the levels of
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all of those systems, you can't say that there's a common level that
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you see amongst all those systems across greenhouses and vertical
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farms. We observed cannabis indoor farms that
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In some cases had manual lighting controls, which boggled my mind, but that's what
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they chose to do. And then we also had one of the most, what they
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touted to be the most sophisticated, completely integrated, completely
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like well-oiled machine-controlled cannabis farm. We went
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to a huge cannabis greenhouse, which had very little lighting and
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therefore did not need a ton of advanced lighting control, but had one of the
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most sophisticated irrigation systems we'd ever seen, where they did
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gravimetric weighing of their plants to see how much water was happening for
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a sample plant that therefore then dictated how much water the rest of the crop
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got. They also had sophisticated energy generation
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systems, cogeneration systems, and absolutely knew a ton about their
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energy. So that's cannabis, and that's just how you can see, like, you've got the
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full spectrum there. It's hard to say what the baseline is. Some people
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have said that when you've seen one greenhouse, you've seen one greenhouse. So in my
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study, I've seen many, but can we say that my study
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applies to everyone? No, it probably just applies to California. But the last thing
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I'll say is that I do think that overall, greenhouses, if they're growing
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a crop that has a lower profit margin, we generally saw have less advanced
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controls. And if you have a crop like we've talked about with
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orchids, there's more of a reason to have some more Cadillac-level
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integrated system. But I think what we do see overall across all of
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them was still generally a fairly low level of system
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energy monitoring. So they've got an idea of how much they're paying
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for their bills, but they— most of them all across the board
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did not have the ability to say, yep, I've been spending $20,000 on lighting,
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$40,000 on HVAC this month, and then in total my bill was
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$80,000. So yeah, that's sort of the gist of it, is like
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the study helped us put more dots on the map, but we still have more
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studies that still need to keep proving that
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there's a general trend for a particular crop. I
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can't really say that yet. So with all this data that you now have
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available, Neta, I'm curious how you think about approaching
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partners to work with. Does this change your thinking about maybe doing an
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audit first about seeing where they're at and what exactly they're measuring? Because
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to Gretchen's point, they may think they've got a robust monitoring system,
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and with the proper audit, you can almost pick out like where
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There are gaps in how they're thinking about this. And then obviously one of the
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questions is going to be, is microclimates going to compete with the systems
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or is it going to work or is it going to complement them? So I'm
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sure those are questions that come up as well. Yeah. So I think what you
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mentioned about the audit, yeah, I completely agree. Gretchen's team and
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Gretchen's expertise and ERI is the perfect company
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that can help with those things. They could step in and take a look at
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an operation and audit them and understand Where, you know, you can even— I
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believe, Gretchen, if I'm not wrong, you guys can even audit their energy bills and
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see if there was some mistakes on their bill. So there's a whole level
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that ERI and Gretchen's, especially Gretchen's expertise, can really
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step in and help operators right away without having to install
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anything. They could just look at documents and papers and bills
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and make sense of it. That's number one. Then number
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2, what you mentioned, Harriet, is Competing or
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complementing? Well, historically, I'd have to say that most
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companies out there have been about replacing, right? We actually come in and
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complement. We're not asking to rip and replace. The other thing that's
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really important is that these energy monitoring systems have to be easy
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to install. If they're not easy install and there's going to be a bunch
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of wires everywhere, it's unlikely that the operators want to go through the
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hassle. And that's where I think what we've done at Microclimates is really
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try to simplify that process. where we bring in a computer with our
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EnvOS, which is an environmental operating system, and these wireless
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sensors for energy monitoring that just connect, hook to the
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circuit level, and quickly begin to monitor your environment. And
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then the operator also has the ability to put in their scheduled
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pricing. So then automatically the dashboard will show you
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how much energy did this pump use How much did it cost
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me? And you have all these beautiful graphs that you can look at and make
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sense of it. Then you start working with a company again like ERI
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and Gretchen's team, and you say, okay, now that you've reviewed my
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baseline bills and what I'm doing, and now that
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I've added a few circuits, I have 3 months of
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data, 4 months of data. Maybe you want to have 1 year of data depending
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on your crop, maybe seasonality, who knows. Now,
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Gretchen, what do you suggest I do with this information? And that's where they
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come in and help you fine-tune your system slowly. And again,
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it doesn't have to cost very much. It's not like we're spending hundreds of
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thousands of dollars by any means. It's very reasonable
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to get to that point and shave off 5% off your energy
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bill, which makes a huge difference. Yeah, Gretchen, I see you
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nodding your head. So what's usually the responses when you show them these studies?
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And obviously, there's always pushback when you have to change systems that are
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already in place. And I'm curious, what are some reasons you'd give a greenhouse
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operator for reasons why they should switch to
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daylight-responsive lighting controls, for example? Yeah, or
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daylight-responsive lighting controls plus some more energy
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monitoring. Exactly. I think that the things that both
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Nada and I try to do is take one step at a time. So yes,
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There's small steps to take, like doing a bill audit or doing
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a quick audit of like, what do you even control? What do you even
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measure? And then I would be able to share with Neta, okay, they
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have this much information. And what we can do together is provide them with
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18:55
more valuable information on top of what they already have. And
297
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18:59
then also provide the right thing, whether that's
298
::
19:03
light, the right light, or the right humidity, or the right temperature. Right.
299
::
19:07
And then lastly, the thing that I care about, save energy. So get
300
::
19:11
more information, get the right target hit, and save
301
::
19:14
energy. Hopefully save money because everyone's energy costs are going
302
::
19:18
up. And so the payback period just gets better the more you implement
303
::
19:22
automation. So we found that sometimes growers didn't know how much light
304
::
19:25
they were actually receiving, right? So they can then tailor their
305
::
19:29
controls to meet production goals, influence plant quality
306
::
19:34
or adjust the amount of light they're doing because they were never actually meeting DLI
307
::
19:37
target, which is something we've found in quite a few greenhouses we've worked with.
308
::
19:42
Then they can use, you know, automation to either
309
::
19:46
do some sort of simple algorithm or use AI, which we might talk about a
310
::
19:49
little more, to decide how much light should I give at any given, you know,
311
::
19:53
15-minute interval. Should I add a little more light because power
312
::
19:57
costs are going to go up tomorrow? Do we have a production goal we haven't
313
::
20:01
met yet? So there's some things that people can start to do to provide light
314
::
20:04
when it's needed or provide, you know, turning it off when it's not needed. And
315
::
20:08
then lastly, you know, the pocketbook. I think that we haven't talked about the numbers
316
::
20:12
yet, but I've been really excited because my study has sort of stood
317
::
20:16
alone along with some academic studies that have been done by like University of Georgia
318
::
20:20
and Cornell University for a while, since like 2016. These
319
::
20:24
academic studies plus the CalNEX study have said automation
320
::
20:28
saves a good amount of energy. And usually that raises
321
::
20:31
eyebrows and suspicion because large numbers usually mean like, how can you really trust
322
::
20:35
that you're gonna save 50% of my lighting energy? That's
323
::
20:39
crazy. But it's not actually crazy. My study, as well as those
324
::
20:43
recently performed by other teams, so the ASHRAE
325
::
20:47
Standard 90.1 committee just this past month presented
326
::
20:51
a slide that showcased 42 to 62% energy savings
327
::
20:55
compared to time clock controls when you implement daylight responsive
328
::
20:59
controls. So if you're paying over 10 cents a kilowatt hour, which
329
::
21:03
many of us are, many of us even at our house are paying more than
330
::
21:06
10 cents a kilowatt hour, the payback can be as short as months.
331
::
21:10
And I heard someone in the ASHRAE committee say this
332
::
21:14
may be the quickest payback measure that we've ever added to
333
::
21:17
90.1. And so I really think that speaks to not just
334
::
21:21
the impact, the magnitude of this opportunity that
335
::
21:25
for the CEA industry, but overall for the whole buildings industry,
336
::
21:29
this is a very big opportunity in terms of energy savings. So that's what
337
::
21:33
I'd say to a greenhouse owner, but also I'd say to a vertical farmer as
338
::
21:36
well. I'd say, what do you currently not know? What do you want to
339
::
21:40
hit for your target? Do you know you're hitting that target? And then let's save
340
::
21:44
some energy. Even if you're indoors, you're probably able to dim your lights
341
::
21:48
in ways that you're not. You're probably able to modulate your fans, your pumps.
342
::
21:51
There's always those tweaks, the continuous improvement that Netta was talking about.
343
::
21:56
5% a year, that'll help you cushion yourself from utility
344
::
22:00
cost increases. And then if you go even more aggressively, you know, if you have
345
::
22:04
a dedicated energy management practice, you could be saving more like 15%, 20%
346
::
22:08
a year. Or you could go big with one thing and
347
::
22:12
over the years save 50% energy savings with larger construction projects.
348
::
22:16
So naturally, that begs the question, Gretchen, how come people aren't installing these
349
::
22:20
everywhere? And I'm excited to hear what Neta says
350
::
22:24
about this one as well. But like, the quick, simple payback does not tell
351
::
22:28
the full story of a construction project, right? Like, if it did, then you and
352
::
22:31
I would be doing improvements to our living spaces all the time
353
::
22:35
because the payback would be the reason we would just do it. But a good
354
::
22:40
reason, I spoke with a grower in the Mid-Atlantic region who still uses
355
::
22:43
high-pressure sodium lights and time clock controls, and they
356
::
22:47
explained that they know every reason under the sun why they should install new equipment,
357
::
22:51
but the disruption to production is just a challenge to orchestrate that they—
358
::
22:55
I'd say the number one reason is operational impacts during construction. The
359
::
22:59
second one I'd say is these systems are not yet industry standard practice because
360
::
23:02
they're not required by codes or published in standards. But as I mentioned,
361
::
23:06
ASHRAE adding 90.1 language to require daylight responsive
362
::
23:11
controls means that, that because it's the basis for codes and standards around
363
::
23:14
the world, anyone could point to that and say, okay, Minnesota
364
::
23:18
chooses to adopt this. Okay, you know, Maryland chooses to adopt
365
::
23:22
this, or even the city of Chicago chooses to adopt this.
366
::
23:26
But it's happening in California at the state level right now. So I think that
367
::
23:29
if you're a California grower, This is the most important thing to know is that
368
::
23:33
it's not industry standard practice now, but by 2028, you're going to probably
369
::
23:36
be— January of 2029— required to do it. And then
370
::
23:41
lastly, upfront cost, right? Even if you get paid back, even
371
::
23:44
if you get a rebate, you've got to pay for materials, labor, commissioning,
372
::
23:48
training. And that's just a little bit too much for a lot of businesses to
373
::
23:51
tackle right now, especially during uncertain economic times. And,
374
::
23:55
you know, Henry from Agritecture posted, just today on LinkedIn about
375
::
23:59
how, you know, things are consolidating. So those
376
::
24:03
who are going to do these projects are going to be the, probably the larger,
377
::
24:06
more historically established companies. Yeah, that trough seems
378
::
24:10
to be a bit deeper than people originally thought. Yeah. Anything
379
::
24:14
to add on that? Gretchen covered it all. Like, I'm in complete agreement
380
::
24:18
that it is. First of all, you know, she mentioned California and oftentimes we do
381
::
24:21
see that states follow California. So that's something to say. I think it's
382
::
24:25
going to happen over time. More and more states are going to adapt what California
383
::
24:29
does and you see Historically, we've seen that in every industry, including the food industry
384
::
24:32
that I was in prior to this. So, I think that will happen. I do
385
::
24:35
think that interruption is really hard for them, and they just don't have the manpower.
386
::
24:40
Everyone's limited right now. You know, you don't have the manpower to make those changes,
387
::
24:43
and interruption to their day-to-day operation is a challenging
388
::
24:47
one for them. But we need to make this accessible too. I think that if
389
::
24:51
we can make it small and accessible and you start one room at a time,
390
::
24:54
it's possible to get there. It's just that you don't have to overhaul the
391
::
24:58
entire operation. You can start with one room and say, I changed
392
::
25:02
the lights in this room, or, I applied DLI in
393
::
25:06
this one room. What was the impact of that over the next 5
394
::
25:10
months? How did that compare to my last 5 months? And if that works, then
395
::
25:14
you slowly transition the change. Yeah, and I think it's important, and
396
::
25:17
maybe you can talk to this a little bit more, Neda, about this ability for
397
::
25:21
growers to understand that they don't have to rip and replace, as you say. And
398
::
25:24
I think they appreciate having the freedom to choose a mix and match
399
::
25:28
if that fits their needs in terms of sensors and tech. So how
400
::
25:32
does this help you think about how to approach established growers
401
::
25:36
who are set in their systems like the example Gretchen outlined?
402
::
25:40
Yeah, every greenhouse is different, right? Every greenhouse has different
403
::
25:43
needs. No one manufacturer makes the best sensors on the
404
::
25:47
market. We know that the technology
405
::
25:50
changes. So, I'd say it's, you know, our philosophy
406
::
25:54
has been you don't need to rip and replace, you can complement. So,
407
::
25:58
it's really coming in as a consultant and understanding from that
408
::
26:02
operator, what is it that you have today? Where are your
409
::
26:06
blind spots? Where do you want to go in the future? And
410
::
26:10
how can we complement what you currently have? So, in other words, let's say
411
::
26:14
back to DLI, let's say that You want to save
412
::
26:18
some energy on your lighting, but you don't have
413
::
26:21
DLI. You're worried about the expense and all the
414
::
26:25
wires that are gonna run around with all these different PAR sensors. How can
415
::
26:29
we address that? And the way we've addressed that is, what if you get a
416
::
26:32
PAR sensor that we can convert to a LoRaWAN wireless
417
::
26:36
so you can move your PAR sensor around? Now you don't have a bunch of
418
::
26:40
wires. Now you have flexibility to move the sensors around. Right. What
419
::
26:44
if you use wireless sensors for temperature, humidity? We actually have a
420
::
26:48
facility right now in Virginia that's doing some study on their blind spots. You can
421
::
26:52
actually deploy some wireless sensors to get to know those blind spots,
422
::
26:55
and you can still take that information, feed into your control system. Whether the
423
::
26:59
2 control systems, their existing control systems that we're not ripping and replacing, can
424
::
27:03
be integrated with microclimates is a different story. But if they can be
425
::
27:07
integrated, then the 2 systems can talk to one another. So really, it's
426
::
27:11
about giving them the freedom to choose what's right
427
::
27:15
for their operation. So I'm a strong believer that, you
428
::
27:19
know, growers shouldn't— they should really own their own
429
::
27:22
strategy, and they shouldn't have any limitations because of the vendor's
430
::
27:26
limitations. And I think it's really, really important that they have the freedom to
431
::
27:29
choose. That's helpful for that context. Thank you. So Gretchen, you did
432
::
27:33
touch on AI, and I'll give you both a chance to talk on it and
433
::
27:37
seeing what's coming up. But based on, you know, what you've seen in your experience
434
::
27:41
with this research, And obviously following the trends of what's happening on the AI
435
::
27:44
front, where do you see the biggest disruptions happening, or what should growers
436
::
27:48
be preparing for? Well, I want to reiterate what Neta said about a phased
437
::
27:52
approach. So no matter what happens next, whether there's this
438
::
27:57
great new innovation like a brain that will tell your control system
439
::
28:01
exactly what to do because it knows the weather for the past 50 years and
440
::
28:04
it's predicting the weather for the next 20 months, And that
441
::
28:08
would be awesome, but that's like also probably going to be like buying a very
442
::
28:12
expensive thing for a while. And so a phased approach, no matter what, will probably
443
::
28:16
be the best. And I think what, you know, the microclimate systems offer
444
::
28:21
is literal like card by card. So you can decide how much
445
::
28:24
equipment do you want to monitor and control with the system versus
446
::
28:28
letting your existing system continue to control some things and monitor some things.
447
::
28:33
And For example, with AI, if you want to first implement
448
::
28:37
a simple daylight responsive control algorithm and say,
449
::
28:41
turn the lights off when the PPFD gets too high, all right, just don't
450
::
28:45
overlight. Then you take a look at the crop, you say, that looks good. All
451
::
28:48
right, let's try now a DLI target, which is just based off of the target
452
::
28:52
you think I'm gonna reach at the end of the day. That doesn't require AI.
453
::
28:56
It could, but it doesn't need to. Folks from Cornell have been writing those algorithms
454
::
29:00
since the '90s. And those are just intelligent algorithms. But
455
::
29:04
AI, I think taking more of the agency
456
::
29:08
of making decisions might be where we start to see it happen, where it's like,
457
::
29:11
all right, the AI's gonna start to tweak your DLI targets day
458
::
29:15
by day because it's decided what you need. And we've allowed
459
::
29:19
that to happen with other things like screen operation. We've decided that, you
460
::
29:23
know, the control systems know what's best for the screens as they read
461
::
29:27
the climate. Responses, like what the temperature is and the humidity is, and they open
462
::
29:31
and close. So I do think that we'll start to see that integrated more and
463
::
29:35
more as we let the growers spend their time
464
::
29:39
doing the more human-valuable tasks. We've started to see the value of human
465
::
29:43
labor compared with AI labor, and that's where I think we'll start to see the
466
::
29:46
balance in the vertical farm and the greenhouses. What's important for AI to do because
467
::
29:49
it's cheaper, and what's important for the grower to do because it's much more expensive.
468
::
29:55
And Neda, what are you seeing from your side? First, I want to completely agree
469
::
29:59
with what Gretchen said, that phased approach, right? I love working
470
::
30:03
with Gretchen because we both have this mentality of things
471
::
30:06
don't happen overnight. It's a phased approach, and you want to make it
472
::
30:10
so it's accessible to the operator and it's scalable
473
::
30:14
so they can slowly work their way there. So from an AI perspective, I
474
::
30:18
think that AI is actually going to be very different than what
475
::
30:22
most people expected right now. A lot of people are thinking of AI as this
476
::
30:26
autonomous growing or yield prediction.
477
::
30:30
And yes, we're going to get there, but I think we're going to get there
478
::
30:33
slowly. And what Gretchen touched on is maybe making those
479
::
30:37
slight modifications in operation, right? To make those slight
480
::
30:41
modifications to your DLI or your HVAC systems,
481
::
30:45
AI needs to have the ability to Yeah. If
482
::
30:49
you don't have the data today and you're not collecting thousands of data
483
::
30:53
points, if you're not talking to an AI and actually
484
::
30:56
getting this— I think of the AI today as an assistant
485
::
31:01
that you hire that eventually is going to become your consultant or
486
::
31:04
it's going to do the work for you. It's either going to advise you, it's
487
::
31:07
going to do the work for you on your behalf, right? But if you don't
488
::
31:09
have the thousands of data points, if you can't summarize the trends, if you can't
489
::
31:13
make any recommendations and alerts, and you can't generate those reports based on the thousand
490
::
31:17
data points, how is this AI How am I going to actually get to know
491
::
31:19
you? So first of all, we have to step back and say, are operators actually
492
::
31:23
collecting data? We already said early on in this conversation they are,
493
::
31:28
but they don't have enough environmental visibility, which means they actually are not collecting enough
494
::
31:32
data, number one. Number 2, is the data coming together in
495
::
31:35
one place, or are these all different silos and the data is just
496
::
31:39
disparate and all over the place? Are you able to pull the data into one
497
::
31:42
place? You should be able to. So that's number 2, is that you don't want
498
::
31:46
your AI to be working inside of those. You want your AI to step back
499
::
31:49
and look at your entire operation and make decisions for you. Number
500
::
31:53
3, can your AI agent talk to other AI
501
::
31:56
agents? Some can, some can't. So you need to have an AI agent
502
::
32:00
that can speak to other AI agents. And then number 4, I'd say, which is
503
::
32:04
the long run, is can your AI with your environmental
504
::
32:08
automation now be able to talk to, let's say, your ERP systems?
505
::
32:12
And that's where we kind of move towards this yield prediction
506
::
32:16
and autonomous growing is when we really first have
507
::
32:19
thousands of data points. We understand it. The AI has
508
::
32:24
conversations with you. I mean, all of us are using chat now, right? A year
509
::
32:27
ago when we were using chat, we didn't trust it. And
510
::
32:31
now our chat or Claude, whoever you're using, knows
511
::
32:35
more about you, the way you look at things, the way your
512
::
32:39
operation operates. Yeah. And now it can advise you. But none of this
513
::
32:43
stuff can happen overnight. It happens very slowly. And you need
514
::
32:47
to be able to trust that AI to make decisions on your behalf. So maybe
515
::
32:51
at first, it's an AI that's going to come back to you and tell you,
516
::
32:54
hey, I suggest you make this change to your DLI. But you have to have
517
::
32:58
a set of eyes and say, I trust you, I don't trust you. Or, I'm
518
::
33:01
just going to do a simulation. I'm just going to do it in an R&D
519
::
33:04
room and see if this works. So when we talk AI, I think everyone gets
520
::
33:07
really excited. And we get really excited as a software company. Of course, we get
521
::
33:11
really excited. We step back and say there's a reality of
522
::
33:14
how it's going to progress, in my opinion, which is more of an environmental automation
523
::
33:19
AI that's going to help you versus the yield
524
::
33:22
predictions. And if you, again, you don't have your data house in order, you
525
::
33:26
don't have your data, you don't have enough data, or you don't have the data
526
::
33:29
coming together, how is the AI ever going to scan thousands of data
527
::
33:33
points to make decisions for you? Yeah, and that's my marketing brain is always on,
528
::
33:37
as you know, Neta. So it speaks to like this idea of like, Auditing
529
::
33:41
or having an audit saying, how data ready are you? How data rich are you?
530
::
33:45
Something along those lines. Because when you talk about these thousands of data points, and
531
::
33:48
I'm sure Gretchen can speak to this, like, you probably have some folks run
532
::
33:52
the gamut of just like, oh yeah, I totally get what you say, or like
533
::
33:55
eyes wide open, like, I'm barely measuring one thing here. The
534
::
33:59
thought of measuring thousands is just overwhelming. So just one quick
535
::
34:03
follow-up for Neda is just with the influx of like awareness
536
::
34:07
around AI, Claude connectors. You know, I myself am like deep in like Claude code.
537
::
34:10
And so every— if you follow X enough, there's always like Claude for this, Claude
538
::
34:14
for that. So are you thinking as a company about making connectors,
539
::
34:18
MCPs? You know, not to get too geeky here, but like stuff that can plug
540
::
34:22
into Claude easily for folks that are already dabbling? Because I imagine a lot
541
::
34:25
of these, you know, smaller shops are seeing how they can do more with less,
542
::
34:29
and then naturally they're leaning into AI. I myself like I've had it build spreadsheets
543
::
34:33
for me. I've had it connect to my CRM and populate it automatically.
544
::
34:37
It's my first go-to now. This thing that I used to do manually,
545
::
34:41
can I automate it? So I'm literally got Claude in a second window, a second
546
::
34:44
monitor, always seeing how I can put it to work. And I'm curious how
547
::
34:48
you think about that. Yeah, 100%. I mean, at the core,
548
::
34:52
you know this about us, Ari, is that we are an integration company. We're
549
::
34:56
an open company. core, the philosophy of Microclimates
550
::
35:00
has always been about not living in silos. So absolutely,
551
::
35:04
we are definitely looking at ways of— and we're already working on some
552
::
35:08
things on AI— is how do you get it to work with your existing AI,
553
::
35:12
your large language models, and then how much information can be
554
::
35:16
shared back and forth. And there's also the security aspect that always has to be
555
::
35:20
considered. So that's what our technology team is really focusing on, is the security aspect
556
::
35:24
and how do you keep that information especially now that you're sharing all of a
557
::
35:28
sudden environmental data, right? We've always believed that you
558
::
35:32
own your data. We don't own your data, which is why we're an edge company.
559
::
35:36
Your data is on-site, on-premise, not in cloud. You own your data.
560
::
35:40
So we gotta be really thinking hard also about the security aspect of it. And
561
::
35:44
that's what our technology team is focusing on. And it sounds like, Gretchen, when it
562
::
35:47
comes to security, that's something that's probably near and dear to a lot of growers.
563
::
35:51
Well, yeah, and it's near and dear to my heart. My mother is, Actually, like
564
::
35:55
one of the kind of mavens of IT security from the '80s. So,
565
::
35:59
she worked for a defense contractor in DC. She raised me to not give
566
::
36:03
out my data on the internet, not talk to strangers, you know, all that sort
567
::
36:06
of stuff where it was like, security is paramount, like operational
568
::
36:10
security for business. When we worked with one of the field demonstrations, Neta, I
569
::
36:14
think it came up that one of the IT teams was like, whoa, whoa, whoa,
570
::
36:17
you're gonna have a gateway and you're gonna be needing to connect to the internet?
571
::
36:21
Like, we've got issues with that. And so, I mean, even just that sort of
572
::
36:24
stuff, even 3 or 4 years ago, now it's funny for me to think that
573
::
36:28
we have companies that are almost divulging so much to
574
::
36:32
companies that aren't even their company. So I might recommend
575
::
36:36
continuing to be cautious with that phased approach, as well as considering making
576
::
36:40
enterprise AIs that are owned and managed by your enterprise, and
577
::
36:44
perhaps not sharing everything with external AIs if you
578
::
36:48
are able to avoid that. I know that there are potentially with like
579
::
36:52
microclimates, there's going to be ways for you to have AI recommendations that
580
::
36:56
are essentially always guaranteed to not be being used
581
::
37:00
to train other growers, for example. I think that was another concern that comes up,
582
::
37:04
and I want to make sure that continues to be something, you know, credible companies
583
::
37:08
do. So a grower I respect once said, I expanded one
584
::
37:12
acre at a time. And I think that person is still in business
585
::
37:16
and will probably be a good guide to think of as we all adopt more
586
::
37:20
automation and adopt more AI. I think everyone should explore their options and
587
::
37:24
find tech that allows for integration of existing systems, whether that's existing
588
::
37:28
hardware, existing enterprise software, existing AI
589
::
37:31
agents. It should be easy to install and it should have a low
590
::
37:35
subscription cost, which I think is something we haven't talked a lot about. But whether
591
::
37:39
it's AI or whether it's a suite of monitoring and controls
592
::
37:43
tools, those all have a cost, ongoing cost these days. It's
593
::
37:47
rare that you find something that you buy it and it's yours now. So I
594
::
37:50
think that the controls market is competitive though, so there's a lot of price points.
595
::
37:54
I'm excited to see that we continue to maybe use those levels of sophistication
596
::
37:58
to help people find the thing that's like right for them. But for me,
597
::
38:02
I personally don't use AI yet. I am maybe going to be swept
598
::
38:06
along in the wave eventually, but as an energy person, for me, I just
599
::
38:10
don't find it something I want to use yet. But I want to support whatever
600
::
38:13
systems people use, whether they're an industrial, ag, or commercial business. Because
601
::
38:17
it's not like, Annette, like you've said, it's not up to me to decide how
602
::
38:20
someone chooses to grow or how to choose to use their data. So as
603
::
38:24
we get close to wrapping up the conversation, Gretchen, I'm curious, when you
604
::
38:28
have conversations with companies in the space who are dipping their toe
605
::
38:32
in the sensor space or trying to revamp legacy systems
606
::
38:37
or hearing these conversations about AI and daylight control sensors, and, you know, a lot
607
::
38:41
of it can start to be overwhelming. So for folks looking to get a
608
::
38:45
start or get a foothold here, what do you usually recommend? Well, I
609
::
38:49
recommend finding free training. There's a ton of amazing free training
610
::
38:53
available from almost a decade or more now of free
611
::
38:56
webinars, short courses by Glaze, the Advanced CEA
612
::
39:01
team, the Indoor Ag Science Cafe. You don't have to
613
::
39:04
go in blind and get sold something by, you know, someone at a
614
::
39:08
trade show. You should get to know people, build relationships, and find out
615
::
39:12
like what's been proven in growers like you. So for example,
616
::
39:16
I've got a grower in California who's trying out root zone heating,
617
::
39:20
and they grow strawberries, and that's not terribly common yet with strawberries.
618
::
39:24
And so I think a key piece for, you know, persuading that grower
619
::
39:28
to try it out was getting utility rebate support,
620
::
39:32
showing them some academic studies, and making them feel like
621
::
39:36
they can continue to talk to other growers who do it. So those would
622
::
39:40
be some of the things I say about building trust. I think that the market,
623
::
39:43
ultimately, people need time. Sometimes my projects take years
624
::
39:47
to come to fruition because there's other things that are going on, like a pest
625
::
39:51
management thing or a delivery distribution thing and
626
::
39:55
trying to get new uptake agreements. So I see
627
::
39:59
things in like long years, much like construction. You just have to kind
628
::
40:03
of not see it as something that's going to turn around in the next 6
629
::
40:06
8 weeks or something. So, Nada, what do you think? 100%.
630
::
40:10
I think it's built over time. It's a progression. It doesn't happen
631
::
40:14
quickly. Yeah, continuous improvement, like kaizen. You know,
632
::
40:18
I think the growers that stand the test of time don't adopt
633
::
40:22
big rocket ships and then go to the moon. Most folks
634
::
40:26
are still on the ground, and someone called it a 7-day farmer.
635
::
40:29
I liked that phrase where it's like they are— that is what they're doing. And
636
::
40:33
that's what they're invested in. And it's like potentially this work, this
637
::
40:38
automation, this environmental visibility that is
638
::
40:42
amongst their priorities, but it's neither urgent nor the top importance.
639
::
40:46
So that's why we have to take our time to find when does it become
640
::
40:49
important. Oh, data centers caused your utility rates to go up by
641
::
40:53
25% and, you know, demand charges have gone up too. Now it's probably
642
::
40:57
the time to do an audit and improve lighting. So to that,
643
::
41:01
Neda, how do you think about conversations with new prospects and
644
::
41:05
people new to understanding this, new to understanding if this is even something that they
645
::
41:08
need? How do you usually start those conversations given everything we've talked about
646
::
41:12
today? New to understanding if they need environmental monitoring or controls in
647
::
41:16
general? Yeah. Oh yeah, I'd say if you're a new operator
648
::
41:20
and you're starting out and you have a greenhouse operation or you have a vertical
649
::
41:24
farm, whatever it may be, at bare, bare, bare minimum, we always say you need
650
::
41:28
to have some monitoring information. Right? You've got to have— you got to
651
::
41:32
understand what your crops are actually feeling and what they're experiencing.
652
::
41:36
And if you have one sensor in a greenhouse, it's just
653
::
41:40
not enough data point. So I'd say to a new operator, I'd
654
::
41:44
say at bare minimum, start monitoring. You don't necessarily need to jump from monitoring
655
::
41:48
all the way to automation, right? The automation is like the ideal place, and then
656
::
41:51
AI automation and algorithms are the next best place that you want to be
657
::
41:55
at. But You can do a lot of this work with just having monitoring and
658
::
41:59
setting timers. You know, we've seen operations that work fine,
659
::
42:03
and they run for a time period at that level,
660
::
42:06
but then they do need to move up to more of a control where you
661
::
42:10
have inputs and outputs. So, you have inputs coming from data, from your sensors
662
::
42:14
that are going to force the output so that your system becomes smarter and
663
::
42:17
smarter over time. So, I don't think that you necessarily need to go and purchase
664
::
42:22
I don't believe, I truly do not believe that you need to start an operation
665
::
42:25
and invest in a $200,000 climate control system. I don't believe
666
::
42:29
that. I think that you can start off with a few thousand dollars and just
667
::
42:33
start monitoring, and then set your controls and automation, scale your
668
::
42:37
operation, go one zone at a time. You don't need to just all of a
669
::
42:40
sudden spend $200,000 and every single zone is fully automated. You
670
::
42:44
can start slow because at the end of the day, you're going to run out
671
::
42:47
of money and you're going to be out of business. So, it's not a good
672
::
42:50
way of running a business. Well, like that other grower, he used the first
673
::
42:54
acre to pay for the next acre. So it's like if you do it all
674
::
42:57
at once, you've essentially taken all that capital
675
::
43:01
out of what could be sort of like a green revolving fund where I'm like,
676
::
43:05
great, I improved zone 1. Now zone 1 is costing me less money to operate.
677
::
43:09
I now have some savings to apply to zone 2 because becoming a
678
::
43:12
multinational grower wasn't done millions of acres at a
679
::
43:16
time. Yeah, that approach of going 1 acre at a time, Gretchen, is interesting.
680
::
43:20
How should growers think about that? Do they need a dedicated R&D
681
::
43:24
space for these sorts of tests? Can they do it with a sectioned-off area
682
::
43:28
of their existing growing space? I'm curious logistically how that would work out.
683
::
43:32
It's easier for indoor farmers to do things like that, I think, because they often
684
::
43:35
will have specific control zones that are already very well
685
::
43:39
separated, have different equipment serving it. Greenhouses often will have to put
686
::
43:43
up makeshift barriers if they want to set up a lighting zone of control that
687
::
43:47
Like Cornell creates these, you know, T's where
688
::
43:51
they have 4 different lighting treatments happening in one zone that might normally have
689
::
43:55
one treatment. And then you might see that in a commercial area as well, that
690
::
43:58
they start trying something out and have to build up makeshift walls. But with huge
691
::
44:02
greenhouses, that's not going to be possible. So I think
692
::
44:06
that's why a larger greenhouse would try it out on a smaller one first, and
693
::
44:09
then, for example, implement root zone heating or implement energy monitoring
694
::
44:14
at whole facility. But even if a grower doesn't have an acre, it's like one
695
::
44:18
zone at a time, I think, is where it comes to every size grower. One
696
::
44:22
room at a time. We do that at home, right? We don't renovate our whole
697
::
44:25
house at once. Generally, that would be extraordinarily disruptive and we'd have no money to
698
::
44:28
go on vacation or do anything else that's nice. So yeah, I think we
699
::
44:32
should take it as we all want to continuously improve so that
700
::
44:36
we are resilient and sustainable. And that doesn't just mean that we feel good about
701
::
44:39
the environment. It means that we're here to do business next year. So yeah,
702
::
44:43
I love what Aneta said about what the plants are feeling because— I love
703
::
44:47
that too. I was like, wow, that's a really good phrase. They're living organisms,
704
::
44:51
you know, they're living things. And they can't talk, right? So
705
::
44:55
these systems, they get insight that allows us to not
706
::
44:59
just save money but to actually have like real, like you
707
::
45:03
said, like almost organic impacts. They can't talk and you
708
::
45:07
can add sensors to get them to talk for you. So you can have
709
::
45:11
leaf temperature. That's how I think of a plant talking back to me, right? Is
710
::
45:15
if I can't— if you can't talk, I love that what you said, Gretchen. If
711
::
45:18
a plant can't talk, can you have a leaf temperature sensor
712
::
45:22
that is going to talk on behalf of the plant and let you know,
713
::
45:26
this is what I'm feeling? And then can you take that information and
714
::
45:30
feed into HVAC system because the humidity is too high in the room? And can
715
::
45:34
you reduce that by 3%? And then it will talk back and say,
716
::
45:38
I'm feeling better because I am in the threshold that I like to be in.
717
::
45:43
Yeah, they will get to the point where the AI is actually speaking for the
718
::
45:46
plants. I think about those experiments when I was in grade school. They would play
719
::
45:49
classical music for one set of plants and heavy metal for the others, and the
720
::
45:52
classical music plants would do better. So is anyone doing tests with music
721
::
45:56
in greenhouses? I can't speak for that, but I bet you a lot of the
722
::
46:00
researchers that I work with talk to their plants because they have shown that does
723
::
46:04
result in better outcomes. For sure. I will admit that I do.
724
::
46:08
I will admit that I have a banana tree in my yard right now, and
725
::
46:12
for the first time in Seattle, it's actually flowered 3 different flowers.
726
::
46:16
Thank you. And we're not supposed to grow bananas in Seattle, but I have been
727
::
46:20
talking to my banana tree. I'm sure it's helping.
728
::
46:24
So Gretchen, I'll go with you first and then Neta, just closing thoughts on this
729
::
46:27
conversation, where we are, or maybe some thoughts about the kind of the space as
730
::
46:30
a whole. We did mention Henry posting, you know, status of
731
::
46:34
what's happening in CEA. So I'm curious your 2 cents on what you see
732
::
46:38
from your perspective. Well, at the beginning of the year, I predicted a year of
733
::
46:42
retrofits, and I think that is what we see
734
::
46:45
happening and consolidation. And that doesn't necessarily mean,
735
::
46:50
you know, rocky situation for everyone. Ultimately, for Neta
736
::
46:54
and I, it means that we can work with people to, like, I think in
737
::
46:57
Henry's post, he said like a fairly well-built greenhouse is a very, very valuable
738
::
47:01
asset always, regardless of what happened to the company that owned it. So,
739
::
47:05
you know, times may change and the owners may shift, but we're there to help
740
::
47:08
that greenhouse become better. And so I think that is going to be an opportunity
741
::
47:11
we continue to do more as the vertical farms as well. How
742
::
47:15
can we get more monitoring and help that overhead costs go down so that whoever
743
::
47:19
takes that asset is going to have overall an asset that
744
::
47:23
is very profitable? And I also, for the rest of the
745
::
47:27
year, I see For my point, I'm going to be at GreenTech Philly. I'll be
746
::
47:31
doing a talk on the opportunities that are being presented by new
747
::
47:35
energy regulations and how that might allow for growers
748
::
47:39
to start exchanging energy with, you know, unique type of buildings like data
749
::
47:43
centers and others. So that could be a cool talk. And overall,
750
::
47:47
I would hope to share soon the results of the NYSERDA research that all the
751
::
47:50
glaze researchers worked on for the past 10 years. So that's going to be pretty
752
::
47:54
exciting. Those are kind of the 2 things for the rest of my year. Okay.
753
::
47:56
Thank you. Nada, what's on your radar? Yeah, it's, you know,
754
::
48:00
Gretchen mentioned the beginning of the year, her prediction. I'd say for the past
755
::
48:04
2 years, our prediction has been that we're going to— integration is going to be
756
::
48:08
the buzzword, and we're beginning to see more and more of that. Certainly, it
757
::
48:12
was a buzzword at Indoor@Con, and there was a panelist
758
::
48:17
discussion with our CTO that was involved that talked about what does it mean to
759
::
48:21
be integrated, Why is that so important? So, I think integration is going to
760
::
48:25
be the ongoing theme for a long time ahead. It's just
761
::
48:29
necessary. So, I think that's going to continue happening, and it's already happening for us.
762
::
48:32
We're going to go down that path even further. We're beginning to see more and
763
::
48:35
more companies that have the more legacy control systems changing
764
::
48:39
their models even and opening up their APIs and making it a lot more accessible
765
::
48:43
for companies to integrate with them. So, I think that thing is going to
766
::
48:47
continue. The other prediction that we've had for the past couple of years, and we're
767
::
48:51
just now starting to get there, is that these LoRaWAN wireless
768
::
48:54
sensors are going to take off in this industry. They've taken off in
769
::
48:58
other industries, but in this industry, it's sort of been, we've had some systems, you
770
::
49:02
know, you've got the Aranet systems, the Arroyo system, you've had other systems in the
771
::
49:06
market, but it's really gonna be about these open platforms
772
::
49:09
that the customer has freedom of choice. And we're hearing this over and over from
773
::
49:13
customers, and they get really excited when they take a look at our website and
774
::
49:17
we have 10 different sensors you can choose from, temperature humidity
775
::
49:21
sensors. You don't have to— you can pick and choose from 10 different vendors, 10
776
::
49:24
different manufacturers. So I think that theme is also going to continue,
777
::
49:28
that there's an excitement for these customers and operators to have
778
::
49:32
the ability to pick and choose what's best for their operation
779
::
49:36
and change vendors if they need to because a new
780
::
49:40
product has hit the market. So we've done a lot of integrations this year. It's
781
::
49:43
been really exciting, new integrations this year. Well, I appreciate that
782
::
49:47
feedback from you both because it seems like you both have a finger on the
783
::
49:49
pulse in your respective spaces about what's happening, where things are headed, because you're on
784
::
49:53
the ground and you're doing the work, working with growers. And I love to see
785
::
49:56
these types of partnerships, and I'm sure there's a lot more happening. So if there's
786
::
50:00
others that I'm not aware of and you need to bring them to my attention,
787
::
50:03
we'll get them on the show as well. But, you know, to see you guys
788
::
50:05
working together is really exciting because you're both bringing your respective
789
::
50:09
specialties and strengths, and it's so It feels like a 1 1 3
790
::
50:13
result here. So I appreciate the work both of you are doing for this space.
791
::
50:17
So Gretchen, best place for folks to connect with you if they want to learn
792
::
50:20
more? I'm on LinkedIn, Gretchen Schimmelfennig, and
793
::
50:24
other social media. I have other lives.
794
::
50:28
And Neta? Same here, on LinkedIn. And you can always go to microclimates.com
795
::
50:32
and schedule a meeting with me directly. Okay. We'll make sure all those links are
796
::
50:35
in the show notes. Thank you both again for an engaging conversation. Thank you. Thanks
797
::
50:39
so much, Ari.