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Satellites over the Strait of Hormuz: space surveillance and maritime security
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Tom Edwards
Foreign.
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Hello and welcome to the Entrepreneurs on Monocle Radio. The show all about inspiring people, innovative companies and fresh ideas in global business. Maritime shipping and security has been thrust into the spotlight in recent months, particularly in in one crucial region, the U.
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S. Israel war on Iran and the
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ensuing Strait of Hormuz crisis have disrupted global trade routes and raised serious concerns about the safety of commercial vessels. As governments and businesses alike scramble to navigate the uncertainty, the ability to detect suspicious activity quickly and accurately is becoming more important than ever. On today's program, we're hearing about a company offering real time monitoring across vast areas of the plan, including at sea.
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Jarko Antila
We can detect all kinds of vessels, whether they are dark vessels or even stealth vessels, in the middle of vast oceanic areas, which is not being done currently at all, very efficiently.
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Tom Edwards
This is the Entrepreneurs with me. Tom Edwards, You're listening to the entrepreneurs. Jarko Antila is the CEO of cuvaspace, a decade old Finnish company building a network of satellites that use advanced imaging and AI to monitor the earth in extraordinary detail. With a mission to have more than 100 satellites in orbit by 2030, Kuva Space delivers timely intelligence to partners on everything from agriculture and climate change to safety and security. Jarko stopped by Midori House to discuss the power of hyperspectral imaging and the race to satellite constellations. He began by explaining to me how it all works.
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Jarko Antila
The history is quite interesting, like where this whole thing came from. It's full of coincidences and also intentional development. But what we are now doing is that we're developing a large Earth monitoring system based on a certain kind of a new camera technology with the idea of being able to actually monitor the earth every day, actually several times a day, everywhere, not only somewhere every day, but everywhere, continuously. And figure out what things are made of on the surface of the Earth. So that's the kind of the basic information. So if you think of like taking a hyperspectral image of yourself, you could figure out what your clothes are made of or if a, a dark spot in your skin is an early stage of melanoma. So the information goes into kind of a molecular level of what things are composed of. So from that info then you can get information on different kinds of what crops are, you know, what crops are grown, are they doing good, are there like some health problems, irrigation problems, fertilizing problems, but then also like camouflaged objects, decoys, what things are made of, if this is an actual tank or a fake tank, so all kinds of stuff and you know, invisible gases, methane, CO2 these kinds of things you can see with hyperspectral and the ground laying kind of raw data that we are gathering is multi use. So you always need to couple that with AI to machine learning to dig out the information. So it's not like really like a visual image, but it's a cube of information that you couple with AI. So we're working with both like satellite and camera technology, but like half of our engineering power is actually AI software development.
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Tom Edwards
And presumably that's because as you become successful at realizing that ambition to gather all of this real time planetary insight from around the entire globe, it's a deluge of data and impossible to manage. You would think trove is that where we talk about the game changing nature of AI? Is it in being able to manage and refine that data to draw out these usable insights? Is that the thing that has changed beyond recognition in the last what, three years? Really only?
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Jarko Antila
Yeah, the kind of like the usage of AI and how it has changed, has changed I guess our vision a little bit as well, but not that much. Yeah, managing huge amounts of data. Now people talk more about fusing different kinds of data sources. I mean we are doing it as well with optical data and radar data to get the insights that the customers want. I mean that's really what we eventually want to do. Sometimes you need other sources of data as well. But it is really in our case the AI is also a lot about managing the, the fleet, the fleet of the satellites and how we take the images, how do we optimize it? Because the way we have realized the camera technology is that it's kind of software controllable in orbit. So we can turn any of our satellites being like an application specific, like yeah, please be a methane satellite for one minute when you cross over this point. So there's this kind of continuous sort of tip and queuing as they say in the area going on that baseline. Satellites are detecting something but they're not sure what it is. So they give commands to the next satellites who then become dedicated search engine for that. And from those we don't need to gather all the data as raw data, but we can calculate the applications in the satellite itself. So we have a lot of calculation capacity. And especially if you think of the oceanic areas, it doesn't make sense to record the oceans because it's like approximately 100% water. So you want to find stuff so you can do like vessel detection in the satellite without saving and downloading all that data. When you have those capabilities built into your satellite so to manage all these in a way, complexities, this sort of logistics challenge. It's more like a logistics software really that figures out like what to do and when to optimize the best performance with least amount of data usage.
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Tom Edwards
Now it's funny you mentioned your customers or clients, I don't know how you refer to them, but one can immediately think of myriad uses for this, particularly many in sort of military space, but also lots of civil deployments as well. Is there a typical Kuva space customer or. I guess probably not really.
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Jarko Antila
Well, you know, we're still in early phase, so not sure if we can statistically say what is a typical customer. Typical customer currently is more like a enthusiastic partner as well, who kind of wants to get along in an early phase, has maybe more knowledge and resources to put in to work with us than just somebody who would just sign up and start getting information. But in the governmental side, yeah, obviously like the different defense organizations or like border control type of organizations, they're both interested in what's happening in quite big areas on enemy activities or suspicious illegal activities, like you know, illegal fishing, doesn't need to be military activities. But then on like agri side, we have both large and small agriculture companies that are interested in crop type identification, like how much of like wheat is grown in this area or if the soil has degraded in these areas and like what to do with that. So multiple kinds of. But it is mostly like governmental and then kind of large businesses who are now currently our customers. We see like in the future when we start getting more and more data and more and more satellites and more and more insights, then we start approaching already like individual farmers in the long term so that they will get directly information about their fields. But we're not there yet. But that's in a way in the long term vision.
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Tom Edwards
And it's interesting because lots of businesses, you know, sustainability becomes something of a buzzword whether in a manufacturing or heavy industry, whatever it is, but actually to really think about the planet and its sustainable or unsustainable resources, having this granularity of information is absolutely critical, isn't it? Almost regardless of sector. I mean that must be very exciting in terms of your potential use cases, your growth story, because everybody will need to know this.
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Jarko Antila
Yeah, absolutely. And that's a, that's an interesting point. When you look at like the markets and the maturity of the markets. I mean you have the defense, they have the budgets and they know what satellites are now they have like huge needs as well. Four years ago we didn't have defense in our strategy at all. But now it's like the majority of business related stuff that we do and that's because of the need and kind of matching what we have. But then we have the agricultural kind of food security side and then environmental food security is pretty. It's quite understandable how the business works. I mean you have insurance companies, you have agro companies, you have governmental players and trading companies as customers. But then on the environmental side, which is probably the most important of those for humankind in the long term the business side is quite fragmented so it's still like governmental NGOs. So there's you know, people talked about this voluntary carbon credit market some years ago that's going to explode into like billions and billions. But it's been pretty quiet around it. Maybe it will happen but it's like, you know, measuring the biodiversity of forests in the world every day, seeing how it works sounds like valuable information and we can do it. But then who's going to pay for it? Is there a global organization that would pay for this kind of information? So that's more difficult question and like one of our public references is wwf, which is kind of a typical customer I guess on that side for aquatic monitoring in that case in Indonesia. So yeah, the environmental bit is very important the long term. But we see that as business it grows the slowest of these kind of three segments.
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Tom Edwards
Yeah, it's really interesting it strikes me and we've spoken to one or two of your sort of contemporaries in this or close, close. Similar, similar kind of space. We're huge fans of Finland here at Monaco of course. Why are Finland so good at doing some of these technologies? They punch well above their weight. Is it because they've got this kind of troublesome neighbour on the other side of that long, that long land border. Why is there something in the water or in the air perhaps in Finland?
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Jarko Antila
Well, maybe it is the water, I'm not sure but. Or the ice, I'm not sure which one at this time of the year. But yeah, I mean I think it's coming partly from how the Finnish society works and also a little bit of. It's a little bit of coincidence as well. We put in a lot of effort in educating the people and you know, they have the free education and all that stuff and we have traditionally been quite sort of engineering oriented country which sometimes good and sometimes, sometimes bad. We had the Nokia boom and I mean Nokia is still a big company but it's not any more visible for the consumers. But that Produced a lot of know how and kind of international, very high level, top notch know how on electronics and consumer products. And then suddenly we had a lot of people founding new companies and it had a big impact. I mean the universities, they were tailoring their student programs to match the needs of Nokia. So for example, this radio frequency know how which is like needed for mobile phone design that like ISI is based on. So that's, we had a very strong heritage in like radio frequency design and so the kind of the SAR satellites coming out of that heritage, but the whole kind of measurement technology and this like physics engineering know how has somehow rooted us in a, in these kind of niches that then somehow happen like, like what we're doing. Hyperspectral imaging is not very common. You know, 30 years ago there was a company in Finland that started developing that to terrestrial purposes and, and that has kind of fruited stuff in the research side and that the research had gone forward and then all these things have like suddenly matched. So it has been a curious coincidence also of technologies that had been developed because of this sort of like an engineering background that we've had. But Finland never really had a strong space ecosystem. We used to work for ESA and NASA projects so that we provided an instrument to a bigger mission but nobody had never send out a satellite. And then one day this one assistant professor at Aalto University figured that hey, now it's time for Finland to make their own satellite. So they made this, you know, Aalto 1 student satellite project. So that was the first, first of its kind in Finland. And like our founders and ISI founders are coming from that project. So it also kind of rooted or like enabled new entrepreneurship type in Finland in the space industry. So I don't know, it's kind of a strangely mixed for like certain niche fields and the remote sensing is really coming from the space from that specific lab at the university because they were very remote sensing oriented. And then the basic technologies are coming from like a longer history in Finland. Yeah, long, long answer to a short question.
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Tom Edwards
No, no, I just, I find it really interesting and it's funny because we, we alluded at the top to your own personal background. You remind us about that because you're so you're coming more from the, from the camera side of things or what's your journey to this point?
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Jarko Antila
Yeah, so I have an engineering background originally. So everything in my career has had something to do with like optical or spectroscopic measurement techniques. So I've either been developing them, commercializing, licensing, making products Developing companies around it or something like this, but that has always been there. So I was developing or I was a team leader at a research center in Finland where we started developing this hyperspectral camera technology originally back in almost like 20 years ago. And then the Aalto 1 student satellite project happened to happen at that time and we were kind of contacted by the Aalto University that hey, would you have some ideas for like a payload for this satellite that we, we want to be able to do a satellite that does something. But I mean it's like it's not that important what it does, but we've heard that you have some good, good stuff. And then we're like, yeah, well we have this thing that we could try. So actually the, the hyperspectral camera technology that we are now using years later at Cuva Space was first introduced in ALDE1 satellite. It was provided by my team from VTT Technical Research of Finland. So that's kind of like my connection. So I met then the student people as well from like the ISI and you know, future KUAS based founders. But then I spun out a company in 2014 from VTC that had nothing to do with space or imaging, but it did commercialize spectroscopic sensors. And we had Bosch, Siemens and Samsung and these people as customers. So we learned how to do like thousands of spectrocopy sensors that would show the same result that benefits us also like years later in this company. But we sold that company. I was the CEO and main founder. We sold that company to Germany in 2020 and then I joined Kuva Space when they had just decided that yes, now we will go full speed to becoming a digital service company based on hyperspectral. So I brought in the, the fresh startup building know how and the camera know how. And then I have space tech educational background from way past. So I was kind of a. Yeah, sort of a good match.
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Tom Edwards
What's the funnest as an entrepreneur? Whether you're coming, you know, more from sort of in academia or in a big corporate or doing your own thing. What's the funnest bit? Is it, is it the beginning story? Is it that startup, that kind of crazy ambition, like a runaway train? Is scale up more fun? Yeah, exits are kind of fun. Maybe. I don't know. What's the best bit?
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Jarko Antila
Yeah, that's a good question. When I sold my previous company I was kind of like thinking for a while like should I go to a big company or should I set up something new or what? And I Did end up to the fact that I do enjoy mostly when the company is still a little bit in the early phase when you are tackling all those like sort of fundamental problems with the product and the technology and try to get to the market and get the product market fit when you start scaling the company. Well, the company that we sold was not that big at that point yet. So it was like 30, 40 people. So I don't know yet how it feels to scale from you know, to 1,000 people. Maybe it's fun but one for another day.
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Tom Edwards
Well maybe we'll find out quite soon.
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Jarko Antila
I hope so.
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Tom Edwards
Well to that point, mark our card for what comes next because we've talked a lot already about potential applications. The reach and the impact of this is so potentially vast. As you said, it could have a democratizing impact on the control of information and global agriculture. That's really astonishing in terms of its possibility. But maybe that's a little bit further down the road. So tell us about how you make sense of, I don't know, sort of short term, medium term. Is it about picking up certain markers either or growth scale, market breakthrough? How do you sort of calibrate the progress of the, of the business from here on?
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Jarko Antila
Yeah, yeah. So when we stepped onto this hyperspectral path there we had like a thousand opportunities. If you think of the all the application possibilities of hyperspectral, there are like a thousand of them and so we can't do everything. So we need to start, needed to start like picking the ones that made sense. So it's this kind of a continuous selection process of what's the capability, what's the market pool, what's the market understanding and where the biggest value is. For example compared to high resolution optical or you know, synthetic aperture radar application and things like that. Because the markets are often very unfamiliar about hyperspecal. It's very like unknown thing. So we always get compared to like whoever satellite company. So we need to kind of both educate and bring the value. That was one of the reasons why we decided not to become a hyperspectral image sales company, but an insight delivery company. So that we don't need to explain, you know, the hyperspectral level. Yeah. When you are gathering, I mean if you have a lot of satellites that are gathering a lot of hyperspectral raw data, then you have the biggest pool in the world for your model training as well. So it makes sense for us to then do the training. But then we need to really select what the insights are and this is kind of the pro. So we work. That's why we also work with, like I probably mentioned in the beginning, sort of friendly companies that want to kind of work with us. So develop, in a way, those insight services, sort of one by one, gathering data, running pilots, running demos, and then kind of expanding. And now the first two satellites, they are still our kind of MVP satellites. So they don't have like all the capabilities that our second generation satellites will have. So we can do certain things with those, but not like the entire portfolio that we would want to. So there's a timing aspect to it that we want to be mindful as well. But it's. Yeah, it's an interesting process where you have the engineering and, you know, satellite building and manufacturing and scaling and funding, and all these need to go sort of hand in hand, very delicately forward. But that's something that I need to manage.
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Tom Edwards
Indeed. I feel like your final answer prompts me to go back to the beginning, and maybe I should have asked you about hyperspectronomy or specific cause. You talked about this idea of diving into the materiality, the content of everything. To a layman's ears. What is that process? How does it manage to achieve that granularity, that level of complexity and realize it? I mean, at the risk of trying to boil down a sort of degree level of understanding into one answer, but how does it work?
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Jarko Antila
Yeah, if you take like any. Any material, basically any clothes that you have, or your skin or, you know, chair or car paint or whatever, they absorb light at specific wavelengths, depending on how they are composed of. In optical part of the spectrum, you can see the differences as typically color change. So that's one. On a normal camera, I take three colors. In hyperspectral world, you can take 100 or 150 colors from the same range. So it helps you to identify things way better than visually. But if you then go to the infrared that you can't see at all, actually, then the materials start absorbing way more and they leave these specific fingerprints, depending on what the material is, to the spectrum of light in the infrared. And hyperspectral camera detects the spectrum. So you kind of have like a 3D image. So you have the image, normal 2D image, but then there's a third dimension. So each pixel is actually a spectrometer and produces this light spectrum. And when you have a kind of a library, so you know what silk or cotton looks like or certain type of plastic looks like, you can do like a lab measurement or handheld measurements and build your Library, then you can compare from the measurements so each pixel you get information on what mix of materials is in each pixel. And then you can form these kind of false color images that, hey, you know, if we search for asphalt roads or certain type of plastic material in the forest, then it's quite easy to pinpoint those out, even though they would be visually completely impossible to see. But it's revealed in the, in the material spectrum. And like gases which you don't see at all, they still absorb the same way light in the infrared with specific wavelengths. So methane looks certain, you know, they absorb certain wavelengths. CO2 absorbs another wavelength. So by analyzing this, you get the information, what things are made of.
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Tom Edwards
That's a pretty good explanation in layman's terms. That was the challenge. What are you most excited about, Jarko? As we look forwards, we talk so much about the potential. I don't know, is there a singular application or a great problem? We talk about global sustainability of agriculture. You know, is there a specific area where you leap out of bed with particular excitement every morning thinking we could crack this?
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Jarko Antila
Yeah, the most, like what I expect most is that we get to kind of ramp our constellation up because we have so much kind of request and that we are really like capacity deprived. So it would be great to be able to serve everybody who wants to be served currently, but we can't. So that's like a frustration in the morning. But it's kind of a, it's a positive problem to have currently. I mean, if we kind of look at the, you know, short term, there's lots of things that we have designed in our next generation satellites, which we will start launching at the end of this year, that have to do with maritime domain awareness. So, so we can detect all kinds of vessels, whether they are dark vessels or even stealth vessels in the middle of vast oceanic areas, which is not being done currently at all, very efficiently. So that's something that we definitely are excited to bring into the, to the market for, you know, figuring out where those like illegal or otherwise not to be recognized ships are going. But then like, if you think of the long term things in the future, like environment, I'm quite interested about this. Like global biodiversity monitoring, for example. I mean, I mentioned that it's not the easiest thing to monetize at the moment, but you can imagine that we can update the tree species or plant species distribution of the world daily. Like how much would that help humankind to manage the bioacids that we have at our disposal and also the transparency. So that can be also monitored by the officials, that the biodiversity is not being, like, destroyed. So those kinds of things. I'm actually really excitedly waiting. But unfortunately it will still take some years for that to materialize, but not too much. I mean, in five years we will have 100 satellites. So then we are up and running.
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Tom Edwards
That was Jarko Antila, the CEO of Cuva Space. And since we spoke, Jarko tells us that of course he and his colleagues have been monitoring hot areas like the Strait of Hormuz, and that interest in Cuva's tech has been of growing interest, whether from media outlets or potential new customers. As a result, Koova's shared satellite capacity model is certainly proving to be very well received. You can find out more about the business by heading to kuvaspace.com. And that's all for this episode of the programme. We'll be back at the same time next week. The Entrepreneurs is produced by Laura Kramer with audio editing by Jack Dewis. If you'd like to contact the show, you can email Laura on lrk. And don't forget to follow us and catch up with the archive of past shows@monacle.com or wherever you get your podcasts. I'm Tom Edwards. Goodbye and thanks for listening to the Entrepreneurs.