 Okay, so sorry about that. Okay, great. Hi everyone. Welcome to the UNESCO Hackathon Open Data and Open Science Hackathon Pitch event here at the Lifelong Learning Institute. So this hackathon was put together here at the First Asia Summit by the United Nations Educational Science and Cultural Organization and especially by the Sustainable Development Goals Bangkok office here, represented by Misako Ito who's here in the front row. We have more judges in the front row who will introduce to you in a moment, but I would also like to mention Youth Mobile which is an initiative in Paris also by the UNESCO and it is represented by Davide Storti here from the Paris office. Okay, so let's go ahead here and see what else we have here now. Okay, the schedule now, for now we are slightly delayed already. So a hackathon and intro of judges, the presentation of outcome, then the judges will withdraw and have a deeper look in the submissions today and already half an hour later we will have the award ceremonies so we are advancing really fast. After that will be the summit closing here of First Asia. So a little bit background, some of you have seen it online, some of you have been at the opening event of the hackathon but I would like to remind you of the goals of this hackathon here and quickly go through this. So for the expected outcome of the hack, the applications or games shall be open source and use open data to tackle the climate change environment and sustainable development challenges that we have on this planet. They shall address one or several of the following requirements. One, respond to pressing environmental challenges at local, national or regional levels in Asia. Two, enable the visualization of data in an innovative and or easy to understand way. Three, mobilize and create engagement of variety of stakeholders and sectors of society on climate change environment and sustainable development. Four, gender sensitive prototype recognizing or encouraging women's participation in sustainable development. So as you can see, it's all about sustainability and that's what we're doing with FOSS anyway. So it's a perfect match here and I would like to introduce to you now the judges that we have here today. So you already heard about Misako Ito and Davide Storti who, like, it's very nice of you guys to actually make this happen here with us again. And then on the right hand side we have Kat Orlman from the Google open source department here who agreed to have a deeper look into the submissions. Thank you, Kat, for joining. Next we have, actually I should have introduced you first but I thought ladies first, Mr. Dr. Kotar Tsuan, director of the Lifelong Learning Institute and the gracious host here of the whole FOSS Asia Summit and the event here today. Thank you very much. Then we have Hon Phuk Dang who has put like a lot of the work here into this event and so the woman behind it, yeah. Thank you very much for joining here as a jury member. Next, like Mr. Vladokolje Babic, head of Case IT at Daimler and Daimler becomes more involved in the open source community here and he also agreed to have a look here at the submissions. Thank you very much. And last but not least with a very deep technical insight here from Susie AI, the founder, Michelle Christen, directly from Germany. Okay, so, well, I'm sorry, I'm sorry, I'm sorry. I'm sorry, I'm sorry. So it's not last but not least. It's like last, how can I go further than last but not least? Last but not least, of course, Dr. Ben Leong. He was actually the first one here today who came over and we just like already like so engaged in the event that I'd like, I'm sorry, I forgot you. It's the Ministry of Education and NUS and you also work on the UNESCO projects together so that's why we have you here on the panel also with the insight into research and the educational area. So actually we have everyone here from different backgrounds and shouldn't be forgotten it's open science hackathon. So that's why science is very importantly here represented. Thank you very much, Dr. Ben Leong. So, okay, so, host, applying data analytics, open data and open knowledge as a reminder for the judges. So judging criteria here, we have scoring sheets. The judges have scoring sheets. You could also like if you're interested make your own scoring sheet that's also on the website here. These are the criteria that we will now judge the pitches. Technical implementation, open data and open knowledge, climate change and environment, usability and UX. It has to work. Benefits to society and market opportunity. We would love to see something that can continue to live after the hackathon. Scalability and replicability. So can it work in different countries and different regions with different people and inclusiveness. We really love to see something that can be used by different people, involves diverse groups, involves different genders. So that would be great. Okay, so here's the team schedule and we are slightly delayed but you can see we plant like only four minutes for teams. We have seen already a lot when we visited your tables here during the hackathon and the mentors gave us feedback. So we hope we will be able to make a good judgment. And these are the teams. So we have 14 teams who really stayed on board and each team has four minutes. This means like we recommend you take like three minutes. We set the timer to three minutes for you. You can sit here in front of the stage and you give maybe the jury a chance to ask one or two questions very quickly and give like a direct response. The jury is very experienced so they will understand the background and like that it's just 24 hours basically that you were able to code. Okay, so these are here the prices that we offer. So we have three team prices and for us it's always like very difficult to say who's the first, second or third one and for us everyone's a winner. So we have everyone will receive the same price back with goody t-shirt and so on a pocket science lab. So you can continue with science here after the event and like one of the prices like amoeba IoT kit or a micro bit starter kit. So you can really get into the depth of open science and open data after the event. Thank you very much and let's start quickly. Mr. Guy also like keeps track of the teams that will come down here now. I will switch back to it. Here are the teams. Weather Guru, Centosa, Just Do It, Cocoa Team, SVM. Please line up here on the right, the first team. So when you see like you're like three teams away, come over here on the right please. So you're ready to start right when the next team has finished. Okay, so that would be that would be great. Okay, so I would like to ask whether Guru to come on stage now and we'll do it then. Torsten here next we will run through it because actually I also didn't introduce myself right. I'm also one of the judges and I will sit down now but like Torsten will run through the teams you know. So please weather Guru is here, Centosa just do it. No, JS do it, JS do it, JavaScript do it and Cocoa Team. Please come here to the right already so you're ready to make your pitches and Torsten will facilitate that. Okay, great. So we'll coordinate the teams Mario, well done and all the best to the teams ahead. Let's get you guys set up. Test, test. Okay, weather Guru. You only have one projector? Okay, kicking off with weather Guru. So team go. Three minutes. Okay, hi everyone. We are team weather Guru. My name is Sharpe and with me we have Said and Yenshen. So before we actually start on what we want to talk about our tool rather, I just want to give some context to what our tool or where our tools can be used for. So this is an image of Singapore in January 2018. So floods don't usually happen in Singapore very often. For those of you who live in Singapore floods don't happen very often. However, based on the data that we saw and collected, in January alone the highest or rather it was raining 25 days and the amount of rain collected was about 287 mm and on average that's about 11.48 mm per day when it rains. And because we know that floods don't happen very often in Singapore, I think the government had taken measures to see where floods can happen or occur more frequently. So what they did was they planted sensors or water level sensors around Singapore to detect floods. However, this isn't a preventive measure. It just tells you there's a flood happening here. It will probably benefit somebody who will find out about this kind of data beforehand before leaving the house, but it doesn't actually benefit anyone else when he or she needs to travel for one place to another. So what we wanted to do is, despite all these sensors, this kind of thing still happens. So what we want to do is whether we can leverage on several open source data to predict future occurrences of floods. So have there been systems to predict floods in the round world that have been? So this is what we found from the global flood monitoring system developed by the University of Maryland. However, it's not really open source data. And even if we wanted to try, we could leverage on the API, but we couldn't. So this is a little bit close or proprietary. And also it's based on stream flow and rainfall. So what we want to do is find out which data sets or which features we could use to predict future flood occurrences. So what we did was we made use of the open source data from data.gov from Singapore. And the features that we used was the amount of rainfall that happens a month as well as the number of floods that happen within a month. These are all historic data. So we used that to predict future occurrences. So we're going to show our application. So this is our application that we created. So on the top, so how we can predict future occurrences of flood is based on the frequency of rain. So how frequent, the number of days rain in a month. But sure. So what we wanted to predict is using the number of the frequency of rain per bank to predict the occurrence of likelihood of floods happening. This is another analysis. So what we got here is the threshold. So in Singapore alone, when we take the highest number of days rained in a month, we used that particular model to predict which threshold or which number of days will there be a likelihood of flood happening. So that's all. So you have any questions? Any questions from the judges? Is this tool something where the public can use it to prepare or is this more of a policy issue tool? So at the moment we used the Excel Google Sheets as well as Tableau. Tableau to visualize the data. Tableau public to visualize the data. But I think during the hackathon itself, we learned that there were other free open source tools that we could use. I think at the moment we only knew that Tableau public was one of the people we were familiar with to use. Okay, so great first presentation. Thank you team. Testing? Testing. Okay, all good. So the second team up is Team Sentosa. You get three minutes and then one minute for questions. If you want another time, I will have to interrupt and stop you. Okay, over to you. Good afternoon everybody. My name is Keith and these are my teammates Nor and Sling and we are from Team Sentosa. So my very first question to you is... Sorry for technical delay. So my very first question to you is... If you were from Vietnam, where would you go to find the job? Okay, I believe many of you would have the same answer that of the major populated urban cities such as Ho Chi Minh City and Hanoi. So for many reasons such as climate change, urban migration from rural areas is a problem and many people move towards these heavily populated urban cities like Hanoi and Ho Chi Minh City. And this creates a steep competition for jobs and creates a strain of resources for the people who are in these cities. And therefore we need to... Therefore our group is fine-dried and our aims are twofold. Number one is to highlight prospects in other medium-sized cities. And in this case, prospects refer to other cities that receive investments in order to develop infrastructure such as water pipelines as well as roads. And secondly, we want to use the highlighted cities to match workers with jobs in these cities. So how do we do that? Let's take a look at our application. So taking a look at our application, you can see that we have used open source data from World Bank in order to find where investment has been going towards in Vietnam. So we have highlighted three main medium-sized cities in Vietnam. And in doing so, we have created a web visualization on our platform which is a web-based application so that all Vietnamese can actually access this platform in order to see where there is potential prospects for jobs. And the second part of our application is to link these workers with jobs in these prospect cities. So in doing so, what we want to do is to work with open source API or API of any other job search engines. In this case, we have tried to use Indeed.vn. And then we will pass the data that we have obtained via the prospecting of the cities and link these jobs with potential and aspiring people who want to move to these cities. And with that, we will talk about the sustainability of our projects. Okay, we feel that our project is sustainable because number one is solved the overcrowding problem in these major populated urban cities and thus easing the resource strain in these cities. And lastly, moving on to scalability, we hope to use open source data and we see contributions from people such as yourself in order to develop our software such that we can accurately create and find prospect cities for these Vietnamese. And if this platform works, it can easily be applicable to other developing countries. And with that, we end our presentation. Thank you. Time's up. Good. Okay, we'd like to take some questions from the judges. Oh yeah, we don't speak Vietnamese. We call it AIU. Yeah, so it's photo time. So many of the data generated were I had to go into the search engine and I manually populated a data table because we couldn't get the publisher key for the API. So we haven't ran into the problem that you have mentioned just now. So that was why we were able to get this set of results. But using that set of results, we have created, we hard-coded, for now we hard-coded a link to the direct website. So maybe you can press the... Yeah, so it's supposed to link to indeed Vietnam. Yeah. Okay, there we go. Thank you so much. So I just want to give a quick tip for the next team. You know that I know that some team have five or six members. If you can skip to say your name, you can save some time. And then you can do it at the end. Okay, great. So next team coming up is JS Do It, Just Do It. And as I said, three minutes for you guys. Good luck. And I'll come to stop you. Okay, hi. So this is the team, Just Do It. And we made our app on something called Enviro Balance. So what it addresses is that we are planning to address the problem of tracking everyday pollutants that goes into the products that we use generally. And also what we are doing is we are trying to create awareness using that data that we are collecting from basically the manufacturer to the guy who is transporting it. And the example would be we are using smartphones. Everyone uses smartphones. So there are a lot of resources that are being used for making smartphones. And there are a lot of pollutants that go out for making smartphones as well. What we are doing is we are keeping track of whatever resources and pollutants are done. And we made our own API and we implemented blockchain there. So let me just show you. So this is our basic application. After getting reloaded, we are mining it. We see that the node is created in manufacture. At the moment, we only have a lot of hard-quoted data. So we are just going through it. I'm going to use mobile, I guess. And these data, we haven't really been able to implement at the moment. So this is submitted. And if you go to users and you go to car section, you don't see anything because we didn't import anything. And if you go to mobile, we see that the pollutants that are the byproduct of making that car and also the resources, obviously it's not word or plastic, it's being used for making cars. But so this is a dummy data which we have. And yeah, so that's about it. Thank you. So this is a set of time. Great to see you guys jumping the blockchain from the audience and from the judges. Any questions? So where is the data coming from exactly? So data depends on what basically we are choosing as a product. If we are taking mobile phones, so there's a lot of data from the internet that gives the resources and pollutants that are being used while manufacturing and transferring the mobile phones from the companies to the labs. That is to get the data from the manufacturers, from the directory. For the questions from the judges, we still have a bit of time for the team. Just do it. Thank you. Sorry, can you just explain quickly how blockchain is used here to which part of the process? So suppose he is a manufacturer. So he has a particular set of data that he should have a particular set of data is what are the things that are being used, what are the natural resources that have been used for making a particular car, if you take that for example. So he would be inputting those data there and we would be keeping track of him transporting it to someone else than to me and I can just see what are the pollutants that are there based on the product which I'm getting. So that's how blockchain is implemented there. Okay. Okay team, thanks very much. Good presentation. Okay, not a lot of time and two days to do a blockchain product but we saw a working prototype here. Next team lined up within all these three minutes sections Coco team, let's get them set up and team, as you know, three minutes. Okay, great. Okay, so Coco team over to you. You guys can start. So hi everyone, we are Coco team here from Vietnam. First we will give some facts and insights about our projects. We are inspired according to a research of World Bank in like of 1995 they said that 90% of disease in the developing country are caused by the polluted water resources and it's caused like a serious disease for the people in developing countries and Vietnam also a developing country in Southeast Asia. So because of industrialization and awareness of the citizens so it creates polluted water and also this is the disease of the polluted weather like cancer, skin disease, hepatitis A and diarrhea, elephantitis and chlorine, kidney stones. And so our team problem statement how can we help to detect polluted water area and wanting a square wet send to the action plan for the citizens who live in the big cities of Vietnam. We view a coconut platform that also on the app and on the web too. And the user can report the issue to the platform and the issue they can report it like water, pollution, air, salt, soil, everything but that we focus on the water first. And so it's with the authorities like government or authorized organization can aware issue using the platform and after that they can make action like online like send information or action plan to the user or also the apply like go into that plane check for the water quality at this area. So this is some of the open source and open data we use like data will contribute by the user and also public to the available to anyone. Okay, we also use the open street map and we will demo some of this. We have a video demo here. And we will have like a, we will chat bot here and that is the salt link to the chat bot and we go type it. It's written so slowly. And it will display like that and have a welcome and we issue the report, we will send the location and report the issue. Okay, so team governor. Thank you. We got a demo. Any questions about you guys? I think the time was pretty good. Go ahead, judges. Over here. So you rely on the user to provide the data do you use any like assisting data set for? Yeah, at the beginning we do not have any data so the user will input the data report and after that the other user can use a public on the website. How did you view the chat bot? The chat bot. How did you build it? Did you use any assisting application? Did you update anything or view from chat? The chat bot that you have here. As view from scratch. Okay, thank you. Who does this data go to and what happens with it? Who does the data go to when the citizen reports it? Okay, well great team effort. Well done. Okay, I know it's pretty hard to demonstrate all the work that's gone on behind the scenes but it's great for the teams to have this opportunity to showcase just the glimpse of what they've been working on. The next team up is SVM, is it? It's right, SVM. Let's make sure you all set up. Okay, so SVM over to you and it's Drop Tables team next. You got three minutes. Yeah, thank you. Good afternoon or good evening everyone. Our team, we did a mobile application. It applies in web, mobile, Android, iOS everywhere. That was everywhere. So we did a project called ISO and why do we need ISOS? Because food and climate are not two different things and this is the carbon emission thing and there is 6.7% by food waste in carbon emission and also there is a country called food waste which results in carbon emission. This is a list of countries food waste is stirred in carbon emission. So we thought food waste is a pitching issue which we should work on and here are some percentage of food waste from all these countries which are concerned about. So what did we do? We did a mobile application which is in the middle between there is plenty of food getting wasted and there are a lot of needy people. The needy people can be an NGO which needs food for the people in the orphanage or anything or there can be fertilizing manufacturing companies who need food waste to create a degradable waste or anything and there might be farmers who can use this as a fertilizer. So food waste is there. People are there. There is something missing in between and a lot of people are coming in picture there. So how did we pull this? Back-end is fire-based completely with similar CSS, bootstrap, very plain, simple JavaScript and stuff and it's available across www, iOS and Android. Using Codewa we just packaged it. So let me quickly take you through demo of our application. I have it in Visor. So the user can key in the description of the food waste. Let's say hackathon food waste. So let's say it's 10 kgs and it expires in two days and it's edible or non-edible, whichever form it is in and it's like home cooked food or from restaurant or from supermarket perishable food or anything. So if I have any special instructions to get there I can key in. So let's say MRT and I can give a pick location button. So it will pick the location. Yes, it picks the location and if I want to upload an image I can choose open up the camera, click a picture and upload the image and if I save info the image along with the location along with everything gets there and it says you're amazing. Yes, thank you. So now these details are added who will use this data. So in the menu if we go there there is an option for find the food. So if you go to find the food and this part I was working on it and time is up. So cover is this and I can set it and if I click on show the places it will show all the places which are nearby. And if I click on any one place and it would show the picture and expiry dates and the time and everything related to that and there is a link take me there and once click on it it has to it will open Google Maps and some small bug has to get to that location. It opens Google Maps. Yes. So the data is in Firebase. Now we have got the data about food waste. We yesterday looked for a lot of data about food waste. We have got data about food waste and this data is used for a lot of analytics which we will be doing. So this is how it looks. A lot of analytics which says the amount of food waste which region all those analytics which we did using Tableau. Okay. Great. Well done. Within three minutes. Okay. From the judges on this topic of food waste. Very good. Again where the data come from? From the users who give the data who using the mobile app we get the data and we do this analytics and get this result. We had some plain data in Excel so that we can perform this analytics with Tableau. So it would give different categories and whether it is edible or not and the amount of waste in kgs. So all these we did with Tableau with some initial data. Once the app runs to the market it will be able to sustain in the market with a lot of data because data is power. With great power comes great responsibility. Yeah. So what like you said you use already existing projects some existing libraries. No. Complete from scratch from HTML to slash HTML. Okay. So it's a web app. Yes. Okay. So I know they are already initiatives similar initiatives like that but they might not be open source. Yes. So is that your angle or do you have also? Yes. We had to we wanted to get the data and make it open source and use tools like Tableau for analysis which would give the government to plan more or NGOs to get the data more because there is a lot of food waste and there is not much people who can use it. So we want to be the bridge as an open source bridge between these two. That's our plan. Okay. So Tableau is not open source but maybe we could use Jason and then like analyze it with Elastic or something. Yes. Okay. Thank you. Thank you. Great. Okay. Super. As you can see a lot of technology going into these projects with Firebase and Codova and well done. Hard to put together. Next team up from what I can see is Drop Tables team which is coming down. Let's get you set up. Reach for me. Okay. So while Drop Tables is setting up team Resto will be next. Test? Hello? Okay. So you're online and I'll give you three minutes over to you. Good afternoon everyone. We are Team Drop Tables aiming to provide aid with an eye view of a region. So what are the problems with open data today that we might face over time? Yes. As you know during our research probably during all your research there is a large number of available open data online and these result in many, many problems some of which is just difficulty to compare data multiple, multiple data at once difficulty to analyze their job conclusions and these result in many, many different downsides such as it's very hard for non-profit organizations such as NGOs and other individuals to target areas that is aligned with their goals and without doing a lot of research. So therefore this result in requirement to have a lot of preparation time a lot of research and a lot of time loss. So therefore we introduce to you AI. So with this we'll be able to compare visualize multiple map data available online and therefore increases efficiency and effectiveness when analyzing data. So here is demo prototype with some data taken from open.development.map. So this is the website. So as you can see here we have taken to use Cambodia as our target site. So this is currently the map of Cambodia with some data available. The data you can you can click on the site here to open the data. So right now we have the electricity coverage as well as the mine casualties. They got both of them are represented while there is in polygons and while there is in a version of He-Map. So the users the NGOs can search the specific areas they want to target at such as I say I want to target a health hazard I can say health hazard check the box and then it will display the health hazard box. If I don't want to show the box I can remove the other values. So let's say electricity. So I'm not using electricity. But now let's say the NGOs want to have a closer look at some of the region they choose. So what can they do? So they can actually simply by dropping a pin let's say I'm very interested in this region. I draw a pin here by clicking on the screen. Now these will basically tell us review the information in the cardboard box here right here. So you show the coordinates as well as some of the information based on data we have implemented inside. So you can see points within coverage there are recent points mine casualty density as well as nearest incident away. So with this NGOs and other individuals can much easily access data analyze data and use data for their needs. Are there any questions? So this is purely a data visualization tool that can be used as a tool by any non-profit regardless of their subject area. Is that correct? Yes. It is a data visualization tool but we aim to bridge this difficulty of analyzing multiple data as there's recovery, relax tool online that really allows us to put multiple data together and analyze it at the same time. Any further questions from judges to this? Visualization platform? Where did the data come from exactly? We took the data from OpenDevelop Cambodia. So it's a format of Matt Jason. So it's a file with all the coordinates and all the various details. As you can see just from the coordinates it's very hard to analyze some of the details on the map. So how can people use it? For example, I can like as an interested party I can embed that in my website or something like that. What's the future usage? What will you do in future with it? That's definitely possible. So as you can see we actually have a repository on GitHub and it is very possible for like other partners to be able to work with us and we can implement it as maybe an iframe like widget within the website. So let's say that they want to focus on a selected amount of data on their website, right? They can select them and when visitors go to their website then visitors will be able to see those data already done like very easily for it. So and most importantly because we are using OpenData that means that our data is also continually updated so that means that our data will be like up to date and people will be able to see the current situation and work from that. Okay. Excellent. Great. Drop tables team. Thank you very much. Thank you very much. Excellent. Good. Perfect. I think it's very useful to have this type of visualization for any type of planning especially in maybe high risk areas or navigating certain terrains. Of course, always depends on the quality of the data which I think is a whole new topic but we're going to move on to Team Resto who's already here and so judges please here three minutes of Team Resto. Hi. Good afternoon ladies and gentlemen. We are Team Resto and we are going to solve a problem that we face every day in Southeast Asia today. So the problem we're going to solve is the recycling. Next please. So this is a common issue you see every day you know in the Southeast Asia region. Next please. And then the reason behind this issue is that public has little incentive to use the sorted recycling and it actually requires a mental effort to sort your garbage. So the solution we are going to present is a thing that combines a deposit machine with a cash bin and by combining them we will get our Resto recycling machine. Now we start the demo. So first we go to our website. The website is called Resto Portal. It's a map of all the Resto machine we have across the region. Now we use Singapore is an example so there are three dummy recycling machine we put on the map and now we're going to demonstrate how the person will use the machine. So this is the screen of the recycling machine and you will tap the dispose now in order to start using it. Now a scanner will open you drop your garbage into the bin and then click scan and our AI engine process the scanning image. So now it details a plastic bottle. You can scan more items for example. For example some electric electrical waste like keyboard it's correctly identified and for example some metal waste like drink cans. If the identification have an error you can also report the error. We will still cap the garbage like tagging it as a data with an issue. So maybe just get one more to go to the end. Yeah maybe we just scan a dummy just to yeah. So no object is detected. Oops I should click the done to yeah. So now after you deposit your garbage what we're going to do is send it for the user to use it. So now we are giving some free gifts like tissue paper with advertisement on it. And now we go back to the our portal so this is a portal we can monitor all the trash we put inside. Time's up. Thank you very much. Okay well done. Great. So over to the judges with any questions on RESTRO's recycling project. Yes we use the Google API so it's TensorFlow based object recognition engine. I can't see the submission of the source code can you please submit the source code in the next minute. Sorry excuse me. In your repository I can't see the source code submitted yet. So can you please submit the source code? Oh yeah I think we submit through a zip folder. Okay. We also have links and we put our source code on GitHub is publicly available. Sorry did I answer your question? Thanks. Yeah we use some pre-trained data libraries so that other people have already tagged those items we use the pre-trained data set. But if we commercialize this idea then we will thoroughly train the data ourselves with our own camera for example. Fake pictures Yeah that's a hard challenge maybe we can try to use multiple cameras that's why I just think it's from different dimensions that could be a solution. From the judges? You have to weight it in the machine finally and to cross check it if somebody put a picture on real barrage engine. Oh yes Great Okay Team Marshall Thank you very much Thank you very much Well done Okay Got me Got that one Okay Got me set Okay So an interesting pivot to recycling and encouraging get a better kind of consumer behavior We're going to move on to Oh that was environmental value Is that right? No We change the name Okay We got a different name What is the name now? Yeah I'm going to bring it up first Okay So the judges are making notes getting ready for the discussion So to correct the name of the team that's coming up is Wisdom Buster I'm going to give you three minutes over to you Yeah Thank you So yeah Wisdom Buster for us something is very important it's to spread the wisdom in this world and particularly in the climate change With that Said it's bringing knowledge to the people We will leverage two big notions Data AI Data is nothing 27 is data Data in a context it's information Analyzing the information you bring some knowledge If you do a lot of analysis you will have some wisdom So what we did is trying to combine a lot of different sources and we will see it's very difficult at the moment but with an interactive tool that is completely done with Python and interactive widgets So open data open source we can bring knowledge to for example develop the opportunities of green energy in the world Let's switch to the deal So easily for example we can fix some dates choose for example one indicator to analyze and here you will have some information so you can see that in time it's evolving here you can see even that all the pink dots are more at the top so that means that there is some global warming in Thailand and we can go even further we have to be honest it's not real data because we don't have enough data at the moment we don't have enough details but what we could do it's to provide some recommendations So where do you implement this kind of energy and we can even see that on the map So we are coming from the raw data that we have to prepare its main thing but as I said we need more detailed data currently all the open data that you have is aggregated data so we'll have for example monthly data so we will find a way to maybe more incentive on this side with let's say gamifications so you will reroute the people giving you some information or you can even monetize that maybe in a second step because you give back wisdom taking their data because you cross the information So everything is open source as I said we have easy access to all this information and it's a tool that is easy to use for everyone So it's a beginning today is very short to present a quick thing to present a global thing but quickly we can do things totally open source bringing all the information together it's a community so we can even find that we will use Google tool we will collaborate with Suzy to have the chatbot to search on this data at the end we can work with education because people can work with us for example to develop this project so let's collaborate all together to bring wisdom on climate change and other topics Alrighty Good Thank you very much Okay, over to the judges Team wisdom Some questions on the front? So is there an application? Here it's a Bokeh application so all Python Bokeh is a specific web application development that you can have locally here it's locally I have a question where's the source code? The source code it has been done with Google Collab so it's based on the notebook widget so you have widgets to have the inputs from the user and after it's all the backend is inside the notebook in the VM on the Google it's a basic machine learning tools it's just a Python notebook there that you can interact with to industrialize it we can put that in a proper web application with HTML or even a Bokeh application in a server as you want it will depend so it's exactly as it has been said before it's like open data we can scrap it from the web connect that with APIs here it's a we didn't have a lot of time so it has been done manually but the main thing is with API is good it's quick with scrapping you have to maintain the code that's why if you have a good community to work on it you can quickly intensify the sources of the information that are not available anymore yeah you can mix whatever it's to show that for example here it's basic but after you can mix information you can even cross information for example temperature and precipitations you can it's up to you to visualize whatever you want and it's also the goal of the experts to work with the business to build the relevant tools for the users okay well thank you for the explanation good thank you very much for the team for them it's been a promise great so I mean a prototype we're working on the local machine perhaps the early stages of what we're putting together and yes the data points is very important I think the big question always is where does the data come from are we using APIs are we using external data providers to bring the data in which is core to this project and core to this UNESCO hackathon so great the next team up is team save Mekong if it's right okay you got your microphone already team save Mekong I'm giving them three minutes for this pitch let's see oh we're just having a short technical issue maybe we will see if we take another team first okay so we're going to switch from a Windows platform obviously perhaps probably the root cause here this technical issue to another machine let's see if this works let's see see okay huh so let's have a look let's see if we bring the next team on board and I'll let you guys see how you best connect so in order to continue the sessions and keep the flow going we're going to have team packs P-A-X-S I'll give them just a minute to set up to perfect here we go set up here we go okay okay you ladies have microphone okay so we're going to skip ahead with the first with the next team team packs also for the judges just to make sure you capture on the right sheet ladies over to you we're going to give you three minutes okay okay hi we are team packs and we decided to touch on water pollution so our problem statement is actually we notice a lack of excess of clean water within the Mekong countries so our mission is to increase the awareness of water pollution so our solution is to create an interactive game that can be used by everyone to increase their engagement while acquiring knowledge it also can increase awareness of water pollution in the Mekong countries to provide real open source information and statistics on water pollution in those Mekong countries so now we'd like to move on to the demo so our data was manually inputted by using data from the open development website which is an open data source so the idea behind this is that we want to combine typing tests and at the same time educate people on what is the current issue with water pollution regarding Mekong countries so let's go down please so over here we don't have much data but we did put in a chart to show that okay this is the kind of information that we want to present here and then we maybe further include more information regarding these countries so now we can move on to the actual game so yeah this is our typing test for our presentation purposes for demo purposes we cut it short but by right the paragraphs are supposed to represent the open data that was gathered from open development so yeah that's all thank you thanks so much ladies to the judges some questions to team Pax so yeah so what do you see as a future use case like how will people use this specifically I guess it's more of just their own awareness and so that they won't be you know throw rubbish in like the beach or something yeah that kind and maybe we could also have a follow up for them after gaining awareness they could maybe have a link to like a charitable organization where they can help them out as well okay let me understand this more carefully yeah so you're going to be drawing open source data from this on these countries and making them into typing exercises right correct right so first of all I think have you found sources whereby it's actually paragraphs of text because even data sometimes it's numbers right and then on the Mac the other thing is actually the other question is also your typing is mostly English right but most of these countries actually English is not the first language so even if you get over data paragraphs of text it may not be the English text so how is it going to work as we did think about it we were thinking maybe we could use a translator so we could translate it to their language and then they could still play the game I'm sorry maybe I missed something I didn't really get exactly the point of the application can you very quickly just re-explain what is what is this doing because I didn't get it clearly okay so basically I don't know if you played typing test before where people actually like there will be a block of text and you just literate it and they'll give you your words per minute so we're just using that idea and making the information itself more related to water purification yeah okay did we did we capture that over there sorry excuse me how can user typing something yes typing test yeah how does it relate to water pollution it's more of because our mission is to increase our analysis so when you do it through the paragraphs of text that they actually type out okay so the text itself it's about water pollution sorry again the text itself is about water pollution yes so you get the awareness of it through this okay yeah for it's for the demo purpose that's why we only put one word so yeah okay okay team thank you much team packs I think that was thank you much applause so I think team packs was really trying to demonstrate something with how they would tackle water pollution from a kind of gamification point of view and a bit of interactive approach on how to educate better behavior and instead of just polluting garbage into the rivers just to keep the things going and and moving the team save me Kong still has some technical issues so while we're getting settled we bring in the next team called team MEDON MEDON MEDON and the team MEDON you seem to be ready so over to you alright so our main problem that we can you hear me yeah so our problem that we tried to solve a lot of people do know about global warming do know about problems in the sustainable development but they ask a simple question what is it that we can do about it if you walk from here to your home or any other place you know how many calories you burn you know how many steps you took but you do not know what you did to save the environment we are providing you that solution we are gamifying the experience to help everyone every single person contribute to saving the environment and that way bring about a societal change so the reasons for the carbon emission that we saw the highest was electricity and heat and the next highest was transportation so right now in the prototype that we have we are using the transport and trying to reduce the carbon emissions from each person due to transport I will hand over yeah so despite the fact that the number of vehicles in Singapore is reducing but still the fuel consumption is really high so if we talk about petrol so in 2015 so around 6 million barrel petrol has been conserved so one barrel is around 196 litres so that is huge ok so if we are using more fuels more fuels are being consumed so the carbon emission will also be very high so the goal of Singapore government is to reduce the carbon emission from 2005 to 2030 as by 36% so if we say that 19% of total carbon emission is due to transportation so our main goal is to motivate people to walk instead of taking car for short distances so we have made an Android app to solve this problem so what we do in the Android app is that we pull your data from Google Fit and we know how many kilometres you've walked and now we have a factor like our data team research and we came up with a factor that converts the number of kilometres you've not used a vehicle into the amount of carbon emission that you've reduced in the environment that normal person would have done so in this app over here we see that kilometres saved is actually the kilometres that you've walked, run or cycle or used any other non-carbon emission means of transport and the carbon emission that you reduce is 0.26 kgs from our research we've found out that the carbon emission an entire tree is required to offset the carbon emission of 1.88 kilos so as you see 1.38 I reduced the carbon emission by 0.26 and we tried to gamify this so this progress bar sort of increases as you walk more and I have the distance left to earn a tree now in the next spot so this awesome I mean great but your time's up team so we've just got to keep it short thank you just hold on to that questions is there open data created or used? we've used data from LTA the land transport authority and data.gov.sg to get all of the statistics for Singapore this used for the conversion factors okay so what are your plans for the future what could you do in future? so in the future is it like here what's written here? yeah this is for the next steps? yeah okay so what are the next steps? in the next step what we'd like to do is that we'd like to build a smart home component so since we saw in the earlier slides electricity is a major source and like the smallest of example once you leave your house your house for 12 hours but your router is always on wifi is always on we can cut down on that your aircon is always on even when we're moving to other rooms we want to automate that and automatically switch it off when you travel out with your phone if you go out of the room we want the lights to be off also certain corporates have something known as CSR which is corporate social responsibility where they are obliged to give 2% of their turnover to a social cause we'd like to engage those markets we'd like to incentivize people and make them gain something from actually saving the environment so we could have like coupons or something like that or probably Amazon vouchers later on if you're able to gain enough traction okay maybe one quick question pardon? I'm sorry yes yes it tells you how much you've walked is that right? yes and it detects automatically whether you're walking in the car yes it does that how do you do that? so we're pulling data from Google Fit as of now so Google Fit has an open API so basically in our app you log in using your Gmail account so we have a lot and after that we start accessing your we ask for permissions and then we start accessing your Google Fit data okay so Google tells you whether the guy is walking or is on the car yes okay I mean I would be interested if that could be implemented as open source for example this feature and especially I find it interesting your ideas with like other devices yeah so I really want to do research if there's any standard out there that can actually like be used yeah I'm sorry I understand yeah thank you interesting point Mario good okay round of applause for thank you so much team and on okay well done team made on this was team and on team and on so team and on was walking free-saving app that we saw just now hello hello carbon footprint that's what you call it okay so on to the next team let me pass it Mike okay this is Bud's life right okay okay so while the judges are still conferring and taking notes we're getting ready to bring the next team which is a bug life is that working okay bug life so moving on to bug life while our previous team is still settling some technical issues we'll slot them in later okay bug life I'm going to give you three minutes we're starting now okay hello everyone this is Manish and this is my team bug life so we are here for the few presenting our solution for the farmer so the title to our solution is Kisan Seva where Kisan stands for the farmer and Seva is there so basically what we are doing we have built a solution which is completely open source built with completely open source technologies and using all the open source and open available data through different government portals to help solve the problems raised by the Indian farmers so in India 50% of the agriculture sector employs more than 50% of the Indian population but it basically contributes to just 14% of its GDP so we went on in search for the problems that basically happen or which are the cause of this so we know we came to know that low literacy levels no known facilities no knowledge and basically no awareness or indicate knowledge about government schemes are the basic problems that a farmer faces so we went on and completely made a new solution to provide the farmer with each and every things so this is the farmer suicide rate in India that part so what is our solution this project aims to create an android application which will provide information to farmers it will help in increasing agricultural outputs and will keep them up to date with recent research government plans and statistics the application will provide existing data obtained from given reference sources and other trustworthy services and since we have done this for Indian farmers so this application is available in India as well so we use Sucia AI for creating a special skill that basically tolerates the problems faced by the farmer which acts as an engine where farmers can go and basically chat to know what they can do in certain cases we also integrated low-clack so that we can give notifications to the farmer just in case if there is some calamity or some drought that is happening so we can fetch the live data from low-clack API and give notifications to them related to agriculture so since we know that not a lot of people have if we concentrate on farmers they do not have much internet but due to digital age they do have android phones so this application is an offline first application the only internet that you might need to use is just to interact with Sucia or to get the live data all the REST application is a completely offline based solution that you can see on the left-hand side of your screen so this is you can basically go and chat with Sucia and these are the three main things that work offline and we have also integrated the call center number that is prepared by the Indian government so that the farmers can go and take help from them so this and we use the completely open data provided by opendata.gov.in provided on the Government of India website so this is what we are presenting here thank you well done still got 15 seconds to go but over to the judges so this is designed to work on low-end phones and consume limited amounts of data yes it is basically an offline first application any further questions from the judges any questions if we're good one more yes how do you think you can replicate that scene all the countries yes basically that was a task what we can do is because we are already using all the open source technologies and open products we can basically different type of skills for example and we can also add various translation methods and translation methods for each and every different countries and with different skills and different parameters we can ask people to come and collaborate with us into making this a better thing for each and every country because as we know that farming can be considered as a root dependency since we all are tech people we can always consider that if a root dependency isn't working we cannot ever think that a country will be developing a farming sector that basically provides each and everything isn't working so this is what we have built so is the the skill for the conversational app already online yes we actually built it during this hackathon so it's you can see that it's a prototype that we built it is available on the skills.soc.dev website as well cool and so is it possible also to speak with it did you try it out already it has all the functionalities like you can even do a speech-to-text the farmer can basically speak and it will automatically convert it into text and the chatbot is also able to speak about the responses as well yeah but the speech functionality is still online at the moment but maybe you are thinking could that be the future to have it offline maybe we can actually maybe try to make it a completely offline application so that would be better as well okay thank you team that's very good round of applause good I think Mario some valid questions around these prototypes and these presentations being real products something that they've developed and the team has committed into the github repositories so it's all about sharing and getting these projects out there and demonstrating these data points great so on to our next team I think this is if I got it correctly Niana this is in-fit so this is infinite this is the last team on your list we are skipping apple pie I think that we did have a great turnout we've got 14 teams in total which is fantastic for this first hackathon of us and so over to infinite I'm going to give you three minutes yeah so we are infinite we are not wasting any time introducing it our project is already on github you can look at our source code so what we are trying to create is a predictive smart contacts for conservation of farmers using open source blockchain technology and IoT so we have looked at the data through UNESCO and we can scale up to all three applications land degradation depletion of water resources etc so this is official UNESCO documentation we would like to add statistics how we our app solve these so basically we have solved the app from both the farmers point of view as well as the society point of view so now first I'll show from the society point of view so these are the questions that we are trying to ask to the community people who help in farming and who help farmers next so like this is the thing we are doing like we are taking an amount for each thing so people invest on like these lands like whoever is farming and if some person doesn't farm or doesn't use an efficient source of farming their stake will reduce farming okay and so okay so this is our website it's hosted in github pages you can have a look at it and like we'll know whether like people are farming this is a data visualization tool already available on the internet so you'll be able to see like whether there is 3 laws or anything it's unworking go to so like we have from the farmer's point of view we also have an IoT based implementation of so farmers have to make their farming efficient so we want them to reduce the farming wastage so what we have done is like we have made a website that helps them record their things and provide a smart IoT based solution so like we'll record all these values from a sensor placed at those plants and they'll collect the data in a back end server which we have done using Django so this can also be used by the others and like if it's already raining like they don't need to order the plants right so they can manually control their controllers or like it'll be automatically controlled by the data already available like you can use machine learning algorithms to improve opponent but this was a prototype you can do and we have like a graph visualization to like when the data comes they'll be able to see that on the web app put maps next page last okay well done just out of time but good effort in trying to demonstrate over to the judges sorry I think I missed the part on the blockchain thing I don't know what the blockchain was doing and I couldn't figure out what the blockchain thing was all about we are helping the farmer like everyone expects to conserve something everyone expects to have some intensive incentives in return so we'll do like from all the image data if someone is doing something good like care let us say that farmers are taking care what we'll say taking care very well of their farms means from the satellite data the amount of incentive will be given to the farmer will be more it will be used as smart contract to deploy that means what you gonna give them bitcoins or something I don't know yeah yeah to do something so what does the smart contract do smart and how is measured that the farmer is sustainable like we are getting like we are getting satellite images we have the like there is a API called gain open gain forestry from that we are fetching the details let me show like we just record it on my laptop like it is not only trees we can extend this to other natural resources also like ponds rivers for conservation of any other resources kind of thing do you suggest to create an ifrium currency for this like we haven't yet we just tested it on our local RPC that's all people can like donate we just selected as farmers as use case that can be extended to all like ponds, rivers, lakes etc any natural resources even we can consider land also is this in some way operable so is this in some way operable so that I as a farmer can apply to get a share on this we need to deploy it on a chain okay okay I think we kind of getting towards the end of the evening so thank you very much a round of applause for our team okay so that was team infinite team infinite I-N-F-I-T infinite Mekong is this one so Mekong is now the last team going to come up and this was team infinite okay interesting to see all the blockchain usage because we obviously still got to find some real-world applications where this technology does work and does go down to grassroots levels so well done and now I think we have this is team save Mekong all up and running okay so your last team to go and I think then we're going to close the session and we're going to give the judges some time to confer over to you so good evening judges and fellow audiences we are team save Mekong and as the title states what it does in general is it predicts the future of air quality through datasets we actually gathered from online sources and we use some analytics from past data we collected from past years the future years data so one of the climate problems we chose to address in the lower regions of Mekong was the rising air pollution and the health issue the people there face okay so the app aims to act as an early warning system so basically it predicts the data from the past all the open data and the past sources we collected from and it generates out future data which the people there can use as a reference to see whether the pollution index is going to exceed in the coming years and from there they can actually take preventive measures instead of like damage control measures like after they found out that the air is actually the pollution levels actually pretty bad for them then they start like taking measures to like fix the problem yes so our device also aims to help to allow stakeholders to contribute suggestions and solutions to lower these countries and communication channels for past all of the measures so these are open data we use and these are some of the platforms we actually used in the web application okay so now I'll take you guys through the demonstration okay so this is our app okay let me just talk about the infographics okay so over here we have data what you see in blue is actually the actual data what you see in red is actually what we have done using our analysis okay and then furthermore okay so over here this is another infographics you can see that from what we see is that we set it as from past years to now if there's going to be more than a 0.1% increase we will mark it in red and then if not it will be in green so yeah so red is over and we have a list of suggestions okay that people can take if they want to people can take if they want to try to implement okay we have add suggestions you can actually add suggestions like okay yeah and then you update inside okay and then furthermore what this does is let's say you have a few relevant authorities and that so you can actually email them by selecting who you want and what ideas you want and you can email yeah and they'll send and they'll send out an email okay well done I think your time's about up okay thanks team save me Kong so the judges last round the questions this is your chance to ask the hard ones so just make sure I understand your app what your app does is that you're reading open source data air pollution historical air pollution and you show those countries that have increased air pollution in red right so that you can let people give suggestions how to improve the situation correct actually my concern is that actually it's not about air pollution I mean necessarily I can do all kinds like water whatever so it's like a general general pollution or whatever bad stuff happening in the environment kind of a system to red authorities so it may not be just air correct hope it creates this automatic feedback system so right where are we analyzing right using the digital network or your network but right so using that we we say usual air quality water quality as we say by our other producers right and using that we can basically in a complete integration with government agencies their government agencies can set trigger points we think that air pollution is going to rise to a certain rate level right so they will set up certain measures say in Singapore maybe in the government to do 30RT rates like 20G 20G to help review the carbon emissions for their market so it will always be the constant feedback and it will always be okay maybe one more question from the judges otherwise I'm going to wrap it up any last question okay have a good yes maybe I didn't probably get no okay there is all this data there is a prediction and you can send suggestions right so how do you see it all these many citizens doing this how do you manage to get citizens to participate in this exercise basically there is two platforms platform of authority however you can see let's say the producer level is high in this case all these are reflected at the app for the users so they don't know let's say in the future there will be the carbon emissions will be high and then so ERP rates but those are what concerns so like you know that there will be for this period of time there will be the subsidies for public transport in that case those are shorter measures so so the predictions are quite you know short in time I mean it's a prediction that goes in the next couple of days so it's a prediction which goes in the next year smaller than bigger because by day it's too short it's too white for that so we are going to set it because from later together for now we have yours okay so a round of applause for the last team team said Nekong okay so that really wraps up the presentations but more importantly still to come is of course the judges discussing assessing which of these teams really integrated these APIs and really demonstrated a workable product we'll give them a few minutes and okay so so we want everybody back here at what time it's 10 to 5 45 and before we get to the award ceremony because the jury has actually reached a verdict I would like to everyone here to applause for these fantastic projects that we have seen here at the Hackathon so it's really been great and I think we just go straight to the to the awards and yeah so we have three winner teams but I have to say it has been like super difficult like it was everything was super tight and there were a lot of pros and cons and like we were thinking how can we create more prizes and what can we do so we hope that we can have more Hackathons with you guys soon and also follow up on what has been done and so we will definitely follow up and think about ideas how we can collaborate with everyone here who has been part of it and continue it and of course you have done this as open source you have used like open data as far as possible but you have also raised awareness that we need more open data so it's a very important message here and it's great that we have the UNESCO governmental organization on board because Misaku and Davide you can go back now and give feedback and like raise the issue like tell people that we need more of this open data so who are the winners like everyone's thinking about and I would like to invite Dr. Leon here on stage to announce the first winner team but we don't have like a second third winner team it's just like a row so we have three teams and would like to announce the winner team and then we'll have a small ceremony here inviting the winner team to the front stage thank you Mario as Mario said it was very difficult decision to make to decide on the winner main reason why we decided was that it went to the go home so we decided we had to set on some people so all of you here have done a really good job and I congratulate all of you okay so it's my privilege to announce the first winner and this is not a merit I think the three winners you know kind of all winners the first one is team from India who work with the farmers it's called Bugs Life right okay okay so while they come forward let me just say a few words I think the the app that they are trying to build is really interesting in the sense that it actually addresses the problems that they face today they use the open source data very well and I think one of the things that is really interesting in their app I noticed was that they actually took into account the localization because they did in Hindi right and they were going to do it in other languages which is very important because this was another team that I raised on about calling this Vietnam data you know but in English which was I think kind of not very applicable so they have done a lot of good work in terms of actually thinking through and sharing that the app really works you know just as long as the governments can give the data so on that note I hope that with this little victory you will continue to do good okay and hopefully actually see this app in production thank you very much I congratulate all of you thank you thank you thank you thank you thank you thank you I would like to invite the other jury members please like come on stage and feel free to congratulate the the winning team and so we have been very impressed a lot of handshaking but fantastic thank you very much thank you Dr. Lyon so I hope you have some time afterwards also to talk with everyone there are a lot of technical questions here that people have and yeah we continue and we have a second winner team that will be represented by Dr. Tat Swan here from the Life Long Learning Institute the director who is hosting also this event and like I know it's a ceremony but I would also like to get an applause for the Life Long Learning Institute for your work and hosting us excellent and as the part of your engagement you are now like also participating here in the Hackathon and handing over the second prize thank you good evening everyone it's my privilege to announce the next winning team Team Restore congratulations yeah good job yes Team Restore is also an overwhelming challenge for us to decide the winning team but we felt that the team has contributed in the recycling arena and it's a very meaningful project and it's also close at heart in terms of Singapore we are trying to encourage recycling and it's also quite unsightly seen you can see from the photograph that our people are not really able to do a good job and with this project that we will see more people being able to really help the spirit of recycling and then putting the various items in the right right way in the right form thank you very much excellent and so it's really great and we have a third winning team and the third winning team will be presented by Misako Ito from the United Nations UNESCO which is part of the United Nations summer office in Bangkok thank you for this team we had a long debate among the jury because it was in competition with another team but we specific value one important point is really the presence of a female in the team and so so the team is COCO team promoting the participation in science engineering technology is a very very important and it's not only for UNESCO but for the whole United Nations agency but in addition to that the project they presented really had a very innovative way to engage the people and to engage the citizen and the civil society together to raise their voice and provide feedback so through a platform so that the people can take action so this really complement another way to to tackle the environmental challenges and we found that project very innovative and very interesting congratulations this was the UNESCO hackathon here about open data and open science and going to continue the moment we wrap it up because we are moving we are all exhausted so there is a bit of a question like who is going to take the lead now was like four exhausting days was fantastic so much input and we would like to get maybe a few questions from you would like to share the feedback form so it will happen in a moment