 Our next presentation is by Alan Steele of UNDP. This talk will look at big data, Indonesian style, connecting communities across the oceans. Okay, if I could just make a slight correction, Kim. I'm from Fisher, and we are actually working with UNDP here in Indonesia. My presentation today is really a lifetime experience in not just the fish industry, but across multiple food sectors. Latterly in my career, I was working with Coca Cola McDonald's. And I came to Bali actually to retire about five years ago. And I was approached by one of the fishing community here who was trading about 50 million pounds worth of tuna fish and blue crab with America. And he asked, he's experiencing problems in his company with regards to the traceability of his products being exported to America. And he said, you used to be the go-to man for traceability. Can you develop something for me that will protect me? And I probably was a traceability company, but actually what he was looking for was artificial intelligence or machine learning based on seven, eight years of collected data. And he wanted to look at a different way of collecting data and to protecting his business. And I started to develop software from scratch with really what was my pension. And based on all the mistakes I had made and all the mistakes that other people had made over the years. And there was many failed attempts, I think I saw over about 25 years of people trying to develop software systems and more and more hype around traceability and a lot of imagery about where the industry was going. But I had a specific specification, I can put it that way, on what this particular client wanted. And we started, I got rid of all the ego of trying to work on the world stage and all the things I've been through in my business life. And I went right back to beginning to the small scale fisheries. 25 million dollars of blue swimming crabs, a lot of crabs. And I decided we had to go and look at the fishermen with the cooking stations, the picking stations, the processing and involve the fishermen from day one. So some basic steps to achieve success based on our experience as it can build an intelligent platform. We started at the beginning. So we involved the small scale fisheries. I was also asked to join another company called Each Mile, which they were building the first mile, they call the first mile, which was an app collecting data on board boats and rewarding the fishermen with a coin, with a reward. And the one thing I did learn was, and I think it's come up quite a bit, I think even in Amos's presentation, you're trying to engage the industry is really difficult. Trying to engage people to share their data is even more difficult. And I certainly don't have all the answers. But what I've built over the past three, four years in Fisher is a very basic system using Android phones, the very bottom end technology. And I've built it on collaborations, trying to engage everybody in the industry. Because my client who is, his client is the third biggest fish company in America. And the main species are yellow from tuna, the swimming crab and octopus. And to collect that amount of data from all these different picking stations, fishermen, we have to generate millions of individual trace codes, QR codes, we call them trace codes, every month because we mark every fish, we give every individual tuna fish this, enters the factory, QR code and follow it all the way through the factory. Same with every basket of blue swimming crab. And not just in Indonesia. Kona, we also work in the Philippines, in Sri Lanka and in India. And these are huge challenges for technology. And it was a huge challenge for me on a limited budget. I wasn't able to access grants, but my client wasn't prepared to pay for the development. And it's a very slow process trying to get money from investors and a soul-destroying process. And I'm listening to some of the other presenters, team fish, et cetera, where they're looking for funding. It's soul-destroying. But we're at the situation now where we're producing about between six and 10 million trace codes every month and scanning six to 10 million trace codes every month. And the client wants to double that production. So we as a very small boutique software company will be 20, 30 million trace codes every month, which will let my client, or let us anticipate pricing for the future. It will let us anticipate we're to source our crab or our tuna and give them predictive analytics. We are also scraping the web but we were pretty unsuccessful at that. But we did have all this data. And just, you know, we take everything pretty logically, you know, that from the harvesting, the processing, the shipping, and, you know, to look into what we're talking about, you know, the UNDP that is working with each mile fish coin company. We've developed a tag and release software suite, which allows us to tag fish that are undersized, put them back into the ocean and record that. And then when we caught again, it's actually, it's in Indonesia, in North Sulawesi. We can then link these fish to our own platform where we're tagging the fish as they enter the factory. So we've got 400 small communities in North Sulawesi, which is thousands of fishermen and communities that are using state-of-the-art software. Each of the fishermen has a mobile phone, a low-end mobile phone, and with minimum training, we're letting them scan data into our platform, which is allowing us hopefully to reward the fishermen for giving their data, which is a small part of a solution of solving the acquiring data that Amos was alluding to. But, you know, the other challenge we face is ditching the future and predicting pricing is based on thousands and thousands of individual animals. And you can see here, this is the octopus platform. And another of the challenges we face was trying to make software look sexy. So, you know, we had to bring in graphic designers, we had to bring in people with UI, user interface experience, and also user experience to make something look good. People getting bored just with numbers, numbers, numbers. And it was one of the things I learned when I was working with Coca-Cola. You know, you can collect as much data as you want, but unless it's meaningful and can actually be used, it was just an exercise in developing technology. And you can see here, you know, locations are a big, big part of what we do. And we just use the GPS on the mobile phone to record where the fish has landed. Most of these are day fishermen. You know, they're not going long distances. And just putting your, we call it eight legs, so it was a bit of fun. But, you know, the fun goes once you start developing this huge amount of data. And this is one of the older versions that I developed. And again, it was collecting all this information to make it look and be useful. SIMP is the sales import one, one-stream program for the American exports. So we produced a unique fish ticket and imported all of that, the collected traceability data into our platform to allow these containers of tuna fish that we're exporting from Indonesia over to the States. And, you know, using a little mobile phone that was less than $100, we're protecting a container of fish that's between half a million and quarter of a million dollars of tuna fish. So, you know, we're working with fishermen that are earning $300 a month maximum. If a company that's trading $300 million and linking it all together. And that's the scale of what we're working with in Indonesia. Thousands and thousands and thousands of individual fishermen are contributing their data. This is the first time I've actually been able to achieve anything with the community of fishermen and link it all together. And the guys at Fish Coin on each mile were interested in working with me because the one thing they weren't able to do was to acquire the interest of the fishermen. The people they wanted to reward were the most difficult people to bring on board. And what I've tried to do with my background as an accountant by profession was to monetize collecting data to reward people for collecting data. And with my partnership and my small interest in other companies, I've been able to find a market for my data and for my customers' data and for everyone to be rewarded in some small way. It's not a coin, it's not a token. It is a token of a reward. We were topping up fishermen's mobile phones by allowing, by rewarding them for giving us their data. So, we've got that working. So, the fishermen are rewarded and then the processes that rewarded again for acquiring that data and the American company pays for that extra traceability data. So, it's probably 25 years of development all in this one platform of Fisher which is now predicting the future for my clients. It's providing, we've got it on the blockchain now. You can see some of the screens here. This is test data, but each individual fish, you can go right back to the individual fishermen for all these thousands of tons of fish that we're processing every month and exporting. And we found also that each of these, this was only part of the list that we were now satisfying with our very simple application that feeds into our platform that was originally to predict just pricing. And I have an interest in the tuna business as well where I'm the CFO and we're using this data to supply all of these points which for me has been a lifetime's work now working in reality. And it's been my personal observation about we're nothing without the fishing communities. I took a route in my working life of ignoring the people that were actually catching the fish. I've gone back to basics and the business is a success as a result of working with the fishermen as opposed to the supermarkets who in many cases didn't really want the information and they wanted it for their sustainability statements, et cetera, but there was never any financial reward for a technology company offering that data, but with the fishermen, it's completely different. And I think with all the parties, and I've listed just a few there, governments, fleet owners, other technology businesses, hotels, the people that are taking money from the industry and are all relying on a fisherman at the end of the day. And for me, technology has now got the ability to distribute the rewards to the fishing industry with giving them information, by telling them where to fish as opposed to when I started 25 years ago where everybody was concentrating and developing technology to hunt the fish, to catch more fish, to process fish more quickly. It's now gone full circle, at least these technologies exist, but the world seems to be focusing on what 15 years we've lost 60% of all animals on earth, fishing, through hunting, by building. And I think now we have the ability with our technologies to stop that and to stop it from the bottom rather from the top. I think I've noted here, one fisherman with a mobile phone in Indonesia makes very little difference, but we've got two million fishermen here with mobile phones that can start to make a difference. And from my retirement, five years ago, I started working 60, 70 hours a week back in the fishing industry, hopefully contributing to saving a little bit of our oceans and our planet. Thank you. Thank you very much, Alan. That was a real life story and very interesting one of that in making people along this value chain being really seen and recognized. And this is something that maybe we just weren't able to do in the past and that you thought tools and developing new tools to allow it to happen. I love your term, monetize the collection of data. And once we monetize anything, you sort of do need standards and an ability for people to be recognized. So there's so much to unpack there and unfortunately we're running short of time.