S02E05: The Quest for Sustainable Food Ecosystems
Dan Marius Dobrea (00:00):
The main challenge was to have a deep understanding of all of this technology in order todevelop my system and to put to work together without any problems.
Kyle Fox (00:26):
This is the Smarter World Podcast, focusing on breakthrough technologies that make ourconnected world better, safer, and more secure. I'm host Kyle Fox. Each episode, we introduce
bright minds and their approach to a more sustainable world. We discuss the opportunities andchallenges they face, and how technology can change the world for the better. Today's episodeis all about drones, and how they can help achieve sustainable food ecosystems.
(00:51):
I'm joined by Dan, the winner of our latest HoverGames challenge: Land, Sky, Food Supply. For
those of you who are not familiar with the HoverGames and the most recent challenge, I
recommend you check out our episode from last October. Past HoverGames challenges haveaddressed other issues facing society, like disaster management and health crises. Dan is thewinner of our third annual HoverGames competition, which challenged participants to innovate
ways to use drones and rovers to help achieve a more sustainable food ecosystem. The
competition offered drone development support to coders, developers and innovators, to use inexploring software and hardware solutions for achieving sustainable food ecosystems in thefuture. Dan, welcome to the pod.
Dan Marius Dobrea (01:37):
Hi, Kyle.
Kyle Fox (01:38):
Welcome, it's so great to talk to you today. First of all, congratulations on winning theHoverGames. There were over 400 entrants, and your solution was chosen, and we're going totalk all about that today.
(01:49):I've personally read through how you built your drone, fantastic writeup by the way, very
detailed, and we'll get to that shortly. First, can you tell us a little bit about yourself? For
instance, where are you from, and what are you doing when you're not building drone
solutions?
Dan Marius Dobrea (02:03):

I'm from Romania, and I'm professor at the Gheorghe Asachi Technical University of Iaşi, Facultyof Electronics, Telecommunication and Information Technology. For me, electronics andinformation technology is my passion and my hobby, so in my spare time I develop different
cool application and systems alone or with my friends, colleagues, or students to help others tolearn and of course to have fun. If you want to know more about applications or systemdeveloped, please check my YouTube channel - i3Drones & iTech for Life.
Kyle Fox (02:37):
And I have personally checked that out and you have hours of videos there. It's a fantastic
resource for our listeners to go check out. So let's start unpacking this a little bit. The
opportunities for smart technology to make farming more sustainable really seem to be as
immense to me as its complexity and our impact in our lives. So you were able to build a dronethat addresses this and help farmers specifically helping to detect grapevine diseases. Can you
elaborate on this because I'm assuming vine diseases aren't something I'm guessing our listeners
know much about.
Dan Marius Dobrea (03:10):
My idea is that all type of crops have different diseases. For example, these diseases aremanifested through the structure, shape, color of the leaves. Therefore, although my system
was developed to identify the vine diseases, it can be used to determine the health status ofother crops in a similar way. There are a large number of diseases. In my project, I focused on
two of them with a very important impact on the vine. The first one is generated by a mitespecies that infect grape leaves. The second one is a grape wine viral diseases. Currently, there
are no way to cure this virus diseases. Now to give you some numbers, many estimates of theeconomic cost of the vine exist. For the second diseases, several losses estimate range from
$25,000 to around $227,000 per hectare.
Kyle Fox (04:07):
Yeah, that is a significant number.
Dan Marius Dobrea (04:09):
Yes. Other estimate consider a revenue decline of up to 77%. As a direct conclusion, thisintelligence system or other similar systems are essential because a timely diagnostic andaccurate identification of disease are decisive for controlling disease spread and assuring
healthy development. Moreover, the early detection of the diseases will determine the use ofpesticide only when necessary with a positive impact on the environment.
Kyle Fox (04:41):

So the ability to come in and treat the vines in a way that is only focused when they need it asopposed to widespread pesticide use, which is going to have a positive impact on theenvironment.
Dan Marius Dobrea (04:52):
Of course.
Kyle Fox (04:53):
The picture of my head is that this is going to be a visual approach. You're going to have a dronethat can look at a vine and decide through some techniques whether or not this vine has aproblem and especially if it's not a curable disease, give somebody an indication they need toremove this vine before it spreads. So maybe we can talk a little bit more about your overall
approach. I'm assuming you started first with researching on what these different diseases
might look like to be able to train your neural nets in your drone to recognize them. So can you
walk me through what are those next steps that you did to get that drone up and flying?
Dan Marius Dobrea (05:29):
The main idea was to teach an intelligence system based an artificial neural network. This is anneural network similar with the one from our brain to distinguish between different types ofleaves. It's like teaching a small child. The texture of this leaf is that of a diseased leaf attacked
by mites. This leaf is healthy and this leaf has a viral disease. This process was repeated 10 ofthousands of times. Eventually the intelligence system based on the video images of the leaves
was able to differentiate between different type of diseases. Next step, right now the drone isable based on the PX4 Autopilot to fly on a predetermined path. The next step will be to use theonboard camera and to estimate the position and the altitude dynamically and to move in thisway autonomously through the vineyard.
Kyle Fox (06:22):
Fantastic. What kind of accuracy rates are you seeing on your trained neural nets after you got
them trained?
Dan Marius Dobrea (06:28):
I obtained around 80% of the accurate identification, but I use a small database, not very small.
It was around 300 images and in each images I have 1, 2, 3, or maybe more leaves and I am surethat these performances can be increased very easy.
Kyle Fox (06:49):

When I think about the size of vineyards, being able to have an 80% rate versus sending humans
down the vine rows row by row is going to be very efficient to be able to use the machine to dothat work for us. In expanding upon that, you leverage the HoverGames developer kit, and I
understand you added components like a LiDAR.
Dan Marius Dobrea (07:09):
Yes.
Kyle Fox (07:10):
Depth cameras to it, et cetera, because we just talked about neural nets, but now it's also about
getting the information into the drone to actually make the decision, make the inference.
Maybe expand upon that. Which hardware part helped you the most and what were some of
the challenges you encountered?
Dan Marius Dobrea (07:26):
The most important component was i.MX 8M Plus development part produced by NXP now
under the name of NavQPlus. This is a small but powerful Linux computer with a neuralprocessing unit able to run the deep neural network on it and also to run the robotic operating
system on the arm processing units. In short, this system was the brain of the robotic drone
system developed. Without the NavQPlus, the system would have been only a concept proofsystem. Based on this development system and mainly based on the neural processing unit, it
became a realtime identification system, a complete solution.
Kyle Fox (08:05):
It also sounds like you needed the processing power to be able to run your neural nets, pull inthe data, but you also had to balance flight time. When I think about a very large vineyard,
you're going to need to have as much loft time as possible. Did battery life and battery size
come into play here?
Dan Marius Dobrea (08:21):
Yes. With my system that was developed, I have around 10, 11 minutes of flight, but the system
can be easily improved mainly because you must choose the right motors, the right propellers,and from my experience with other type of drones, you can easily increase this flight time. But
in this competition, I do not have enough time to improve this and this will be done in the futurecertainly.
Kyle Fox (08:51):

Makes sense. In fact, some of the videos that you've created, I've seen you've done analyses on
various types of propeller designs to be able to increase loft time, decrease noise, et cetera,which seems like that would come into play here. We've talked about neural nets and the actual
hardware. What was really interesting to me is that while you were developing this drone, I
noticed that you actually did some work to help make that hover drone more robust. It sounds
like you encountered some EMI issues. Was that actually one of your most difficult challenges orwere there some other general challenges that you needed to tackle that you can talk to us
about?
Dan Marius Dobrea (09:26):
In my previous competitions, the electromagnetic interference was a big problem. To give anexample, I lost one of my drones in a wooded area. But one of my goals of this competition wasto solve this problem in order to be able to flight without any kind of problems, but in order todevelop this kind of application, several cutting edge technology need to work together.
Technologies as robotic operating system, machine learning, neural processing unit PX4Autopilot, MAVLink, Linux operating system or stereo deep sensing. Therefore, the main
challenge was to have a deep understanding of all of this technology in order to develop mysystem and to put to work together without any problems.
Kyle Fox (10:10):
It does sound like there's so many things that meet just to be able to create this solution. We've
talked about hardware, software, training neural nets, understanding the science, the vinediseases themselves, taking action on it. It's quite a complex problem that you've developed asolution for. I'm going to take us in a different direction a little bit. We've talked a lot about thesolution and this is just out of curiosity for me. I come from a farming family and I know fromexperience there's a lot of potential crops that could benefit from your approach. Did you know
at the beginning you wanted to invent a solution for vineyards or did you also have other ideas
and if so, what were they?
Dan Marius Dobrea (10:52):
From the beginning, I aim to develop a dedicated system for the vineyard. The initial proposedsolution was composed of two components. The first one was based on an intelligent adaptive
directional spraying of pesticide. The second one was a system presented previously to detect
diseases through the leaves. This competition includes a significant research component, but
the research to develop an innovative product may or maybe not succeed. So I propose thesetwo components to have a little space and to have a backup solution. The second system wasfully implemented while the first one was only developed around, I don't know, let's say 30%
due to several technical difficulties. If you allow me little advice for the future competitors. In
this competition, the basic idea is that you have to be flexible and to be able to choose thesolution, the path where you get the best result within the existing constraint, the hardest one
being the available time.
Kyle Fox (11:54):
That makes complete sense. Advice being when we're going for it, try to come up with a solutionthat you can prototype because in essence, you're plowing the road for other people to follow inyour footsteps, and what I'm hearing from you is there's a lot of potential here and you cansolve a time problem by putting more resources and development resources, money into thisapproach to be able to get the same benefit. That's really interesting because farming is
notoriously complex, widespread, and we are highly dependent upon it, so making it moresustainable isn't just the right thing to do. It's really necessary for our survival providing food forthe planet. In talking about this applicability to grape vines, what are some of the otherpotential opportunities? You talked about pesticides, that really piqued my interest in being able
to perhaps reduce our reliance on pesticides, being able to identify diseases earlier and taking
corrective action. So what are the other potential opportunities do you see this technology
playing in sustainable farming? Are you for instance, personally hoping to continue innovatingon the farm?
Dan Marius Dobrea (13:05):
If we speak about the technology development from years ago, the technology was able todevelop by itself. Right now it is not in this direction. You must use different parts of different
concept for different domains in order to build an application. For example, the IT technology
plays a vital role in the development. Everything, for example, from medicine to agriculture, butwith one note. IT technology must be made for people based on the moral and ethicalconsideration. I can give you many examples of potential solution in agriculture, but I challenge
all the listeners to read the great solution proposed for this year's HoverGames competition andthey will have a much more complete and accurate picture that anything I can say right now. As
for your last question, the answer is yes. I want to apply for a national competition for research
projects in my country to complete the whole system as I originally designed.
Kyle Fox (14:09):
Dan, this has been a fantastic discussion. I'm so excited about the technology that you've
pioneered and your clear willingness and spirit to want to take it to the next level and I'mlooking forward to seeing what you and the people that follow you are able to create. Before weclose though, we always ask this question. Through your eyes, I'd like to understand how do you
envision a greener world 50 years from now? What does that world look like to you?
Dan Marius Dobrea (14:36):

It isn’t easy to say this. In 50 years, I envision a world where sustainability and environmental
protection will be top priorities. I see the use of renewable energy source like solar, wind,hydropower and other form of energy unknown or inefficient right now. Maybe energy will beextracted from the solar wind, the cost of such energy will be cheaper and even I wish that thisenergy to be free in order to support an equal development of all countries. From theagriculture point of view, maybe the agriculture will be more sustainable. Farmers will shift
toward sustainable farming practices that will reduce the use of harmful pesticides andfertilizers and they will prioritize soil health and biodiversity. For example, in principle, there will
be a return to the agriculture made by our ancestors, a natural one, but based on and supportedby all the existing technology at that time, integrated and compatible with the nature and thepeople of that time.
Kyle Fox (15:46):
I love that vision and I love what you said there. We want to go back into the past to be able toensure our future is the way I would describe what you just said and the idea of energy being
low cost to free to make it equitable so that everybody can benefit from it. I look forward to theworld that you see and I hope that we all can journey toward that. Dan, it has been an absolutedelight talking with you. Keep doing what you're doing. You're out there doing something
wonderful and I hope our listeners have gotten some great insight on this and I highly
recommend that you go look at the HoverGames competition and the results that Dan put
together as well as his own videos about drones and all technologies associated with them.
Thanks for listening and we will be back soon with another episode.