 So you have probably seen this picture before. This is the Pollution Cloud over Madrid on one of the bad air quality days. And I wanted to start with this because I think it's one of the major problems in health right now. And I also have a quote of the Environmental European Agency Executive Director. He basically says that large parts of the populations are living below air quality standards. And to fix that, Europe has to go beyond the current laws. I also have one for America. So the Union of Concerned Scientists of America, they estimate that half of the population lives also under health air quality standards. And in some Asian cities, the situation is even worse. So for example, in New Delhi, in the poor air quality days, they have to stop every construction work to stop spreading the dust. So as I said, we feel pollution is one of the major health problems today. The World Health Organization is estimating around 7 million deaths related to this. And it's causing low life quality and health problems. So some cities are taking actions against it. I have some European examples here. Amsterdam will ban petrol and diesel cars by 2030. Also Madrid, Paris will do the same, London and New York. We have also Sweden that is going to ban the sales of fossil fuel powered cars. There, Norway is going to do the same by 2030. And this is because the members of the European Parliament vote for a 40% cut in car emissions by 2030. So all this is why I wanted to talk a little bit about data intelligence and how to drive electrification forward with it. I work for GeoTap, he said. And in GeoTap, we produce our own hardware. It's that device over there. And it connects to the OBD port of vehicles, of commercial vehicles. So we collect from GPS to load other different data. You can see there on the top, that's how a day of GPS of GeoTap looks like in the world. And I'm going to tell you, I also introduced the topic. I'm going to tell you a little bit about what data we have and how we can use it to help electrification, what is our current electric vehicle approach, and of course, about fleet electrification. You will see some pictures like this over the presentation. This is just GPS dots on an empty background. It's no map. I hope some of you recognize this city. It's Madrid. And we have right now over 1.9 million devices connected around all the world. With those, we are collecting more than 40 billion data points per day. It's not just dots in the map. It's not just GPS. We are collecting a lot of other things. We have weather. We have driving behavior. We have acceleration. We have engine faults. Like, you can know if the ABS is wrong. You can check also. If you have a problem in the clouds, and we have engine status data, of course, like fuel economy, fuel consumption, fuel level. We also have outside temperature, oil temperature, some maintenance status also. And we also have tire pressure, for example. So we have been helping fleet managers to improve road safety and to reduce cost of their fleets. But we feel like we can do more. And that's why we started exploring what we can do in the data side. So one of the things we can do is take some small pieces of information, like windshield wipers, temperature, hash braking, and turning it into sensitive data sets. Like, for example, what are the road conditions? How is the traffic? Is there going to be any risky areas for traffic? And with that, we can turn the vehicles into sensors on wheels. So it's not just traffic. We know we can know how the weather is. We can detect risky driving behaviors and a lot of other things. We want to be a data driving company. So we believe a lot in collaboration. And it's not only us, but trying to build an ecosystem. That's why we launched data.jota.com, where we divide the world in very small areas. And we get a lot of information about them. And we have it for free on that web. Anyone can register there and work with that data sets. I will tell you very fast some of them. So on the bottom here, we have an example of hazardous driving areas. We can know in a city in which areas people is doing more hash braking, more hash cornering, and hash accelerating. And with that, we can identify in which areas people is driving below the standard, or where the driving is worse. And we call that a hazardous driving areas. Another example is the cell coverage. Our devices have a syn card connected. They send all the information to the cloud. So we can know in which areas most of the devices are losing connection. And we call that a cell coverage dark spot. I have an example here of Madrid. The worst part of Madrid is that one in red and black. That, curiously, it was the N15-year Canada del Real. So if anyone know that, it's not very surprising. Other thing we are doing is in weather. You have a map there, like how an hour of weather prediction looks like. That one is maybe the most surprising one. Normally, cities have two or three meteorolike stations. We have thousands of vehicles moving around all the cities. So we collect the outside temperature, and we can map the temperature in a city, hyperlocal. That's something not many people can do right now. And we have other things. We have road impediments, intersection insights, have location analytics, like where people is refueling, where they are getting their cars fixed, where they park the tracks at the middle of the day when they are working. A lot of other things. And with that, we can do even more. For example, there we have a real example in Chicago of what we are doing with the government there. So we can predict dangerous driving based on our two data sets of hazardous driving areas and temperature. We can know if there is going to be a snow. There are going to appear some risky driving areas. Or if everything is going to be fine. The middle one is an example of San Francisco on the hyperlocal temperature. I don't know if you have feel it. You go from one street to another. And then it's like five degrees colder than before. It depends if you are close to a river or if you are close to a park, how tall the buildings are. It can depend on many different things. That's very useful for the North countries because they can know to which street they should go before any other to put salt on it when you have ice on the road. So it can help prioritize. And of course, we are working a lot in the movement patterns, trying to understand how the city flows, how the city works. For example, in an area, this is an example of how we detect intersections. So we can know in the same area which intersections generate more traffic, which ones have less traffic. And maybe we can help planning the route to the ones that are with less traffic. And also, of course, we are trying to get even deeper and understand how a vehicle works. It is an emergency vehicle. It is maybe an school bus or an office vehicle, a delivery vehicle, and trying to understand what type of vehicle it is. And we can tell you if your vehicle is fitting what it should do. So I will have more things. But I think you now have an idea of what we can do with our data. Does anyone know this city? Yes, that's Barcelona. It's again no background, not map. Only GPS dots on a map of one day. So in JTAP, we also have some experience in electric vehicle. So we have an entire office dedicated to electric vehicle that they were before building and designing electric vehicles. So they know a lot of the date of the electric vehicles. We help fleet managers. We give them the state of charge if it is charging north. A lot of, say, engineering status from the electric vehicle. But we want to do more. We feel electric vehicle is one of the biggest things happening right now in mobility. So we want to try to help fleets understand if they can go electric. That's why we launched just a couple of weeks ago the Electric Vehicle Setability Assessment. With that, what we do is, if you wanted to change your vehicles today, we analyze if you could do the same job with an electric vehicle and if you could save money doing so. We feel it's our responsibility to help people go electric. Electrification, as you have seen, cities, the most important measures they are taking against pollution are related to traffic and to road. And to the road, about 1.4 billion cars are in the world and 20% of them is estimated to be commercial vehicles. We know a lot about them, so we can help electrification that part. This is for the first steps. We want to help from 0% to 100% electric, but this is when you want to start going electric, maybe from 0% to 10%, 20%, 30% electric for your fleet. So what we do is, we take the three last months of information of your vehicles, we process it, and then we compare it with an alternative for electric vehicle, like shadowing, doing exactly the same job. If you could do the same job without having to charge midday, just charging overnight on your maybe on the house or on the base of the fleet. And then we also analyze if you are going to make savings, because if you are making savings and it can do the same job, then why don't go electric right now? And this is how the result, a summary will look like of the result. This is with some vehicles from Geotab. So it's our own vehicles, employee vehicles. So it says you how many vehicles you could go to battery-electric vehicle and how many vehicles you could go to plug in an electric vehicle. And it recommends you which models, which makes. It also tells you if you can, if you want to change the price of the car, because you have an special price, or if you want to add the bonnification from the government, you can do it so. This one is a little bit more difficult, but this one is London. So we have seen the pollution problem right now. And what are some of the measures, how it's affecting health. We have seen how electrification could help a lot, reducing that pollution. And we have seen how Geotab treats data, what we do in big data, and what we are doing in electric vehicle. When we were seeing the electric vehicles etabiliate assessment, we wondered, like, why don't we do that for all our fleet? Why don't we look in a big data way to this, try to replicate this? Because you see now a lot of arguments in the network, like, you can go electric, you can, what are the problems? Are you saving? Are you not saving money? So just let's take a look of a big sample of vehicles and see how we can do this. So first of all, of course, I met with some of the electric vehicle experts we had, tried to understand what data we need for this, how we can use it. So the most important thing is the aggregated vehicle usage data. So just collect how the vehicle moves, how it works. I collect data from the last 18 months and how they move every day, how they store, what distance they are doing, what type of vehicles they are. And I collect all that, and I also collected full economy data. So to understand how much, that's very important to know if you are making savings or not, how much fuel they are using on their daily jobs. As you can expect, there was a lot of cleaning in this data. I spent a lot of time cleaning this data to be able to integrate it with the, with detecting the vehicle type. That's very important. So right now, we think we don't have a very good offer from OEMs for heavy trucks of big bands of vehicles. So you cannot really change a heavy truck for an electric vehicle. Maybe you have one or two options, but you really don't have a big offer where you can choose the differences and you can really select the vehicle. So it's very important because right now, you only have a wide range of electric vehicles for passenger cars, SUVs, and light bands. So once we had that, I met again with an expert this time from the electric vehicle suitability assessment side. Just talk with him what features is he using and how he can turn my data into that. This was the most time consuming part, the feature engineering. That's normal. So again, a lot of cleaning, feature engineering, preparing everything. I end up with more or less 60 different features. And once I had that, I added the electric vehicle info that we have of different makeup models. We have the average range, the worst range of the vehicle, the price, the availability in the different countries. We have the energy consumption that is also key for this of all the different makeup models. And I added that. So I compared all my internal combustion engine vehicles with the electric vehicles. The next step was just not comparing with every electric vehicle, but selecting the best match. That's mainly based on range and consumption. So a big part of this was also analyzing every different country, the price of fuel, the price of energy, and also the price of the vehicles. And once I had all this, I could really compare. Once I have for every internal combustion engine vehicle, the best match of electric vehicle, I could analyze if that vehicle can do the job or not. And how? So the first thing I wanted to do was just doing some percentage of how electric ready are we or we are not. I did it with all the vehicles I got in my analysis. Those are 1.2 million vehicles I analyzed. And the percentage at the beginning was not so big. It's 2.38%. I will explain to you the different categories now. But the electric vehicle ready, that means I compare my internal combustion engine vehicle, I check every day what distance it's doing. And I check that 100% of the days that distance is below the worst case scenario of the electric vehicle. So not just the average, but the worst case scenario. So I check that if you are in very cold conditions using the heater and everything, that you could do every single day of the last 18 months the same distance with an electric vehicle. That's the first part. Second part is analyzing cost. So I did an estimation of around seven years, 200,000 kilometers of use of the vehicle. That's the life. And I compare cost for all that life and for the last 18 months. So I compare the cost of the electric vehicle versus the internal combustion engine vehicles. I compare in that country the cost of fuel versus the cost of energy. And what exactly, how much fuel that vehicle was using and how much energy is going to use to do the same kilometers. And of course, I added the maintenance cost that it can differ between the different vehicles. But still the percentage was very low. Then I checked plug-in hybrid electric vehicles. For that, I took a very environmental friendly approach. So I suppose that you are going only to use the combustion engine only 20% of the days. So 80% of the days you have all the distance below the worst range of the battery of the plug-in hybrid. The batteries are very small, but still 80% of the days. So you can see it's a small number. And then I compare the savings. If you use fuel and you use energy, or you use only fuel and also the price of vehicle and all that. And then I checked because maybe you can change to battery-electric vehicle. But you are not making savings. But some governments are offering a lot of modifications now. You have free parking everywhere. So maybe it's still worth it even if you don't save money because at the end you are going to end saving up money and other things. So that's battery-electric vehicle ready without savings. So the first important thing we get here is that almost every time you can change to battery-electric vehicle by the end of the life, the most normal thing is to end up with the savings if you can feed the range and everything if you have a good match. But I was in this very slow. And that's because something I told you about before is the vehicle type is very important. Here I am comparing heavy trucks with electric vehicles off of course. Even if it can do the range, a heavy truck is not a match for a light van. So I then check again but only looking at similar vehicle types. So passenger cars, SUVs, and light vans. And now we can see the battery-electric vehicle already going up to almost eight and in total at 10% that could go electric today. That's 100% of the days doing less kilometers than the worst case scenario of the electric vehicle. But then that's, I'm being very cautious here. Maybe we could do a little bit of sacrifices. Like the governments are taking a lot of action here. Maybe they are going to improve the charging points. So let's check. Maybe if you only 5% of the days, you have to stop midday to charge the vehicle. Only 5% of the days. 95% of the days you are below the worst range of the electric vehicle and 5% of the days you stop. Then you could change 21% of the fleet to battery-electric vehicle and having savings doing so. And just going a little bit more, maybe you can do 10% of the days. Maybe they have a long stop for lunch or you change drivers and they can go back and charge the vehicle for a while. So 10% of the days charging the vehicles, 90% below the worst range. So now we got almost 30% of battery-electric vehicles that we can change. That's a lot. This can be a huge impact on air quality. So I decided to take a look also some like the same numbers but by country and by city. I have some highlights from here. So the first one in blue is when you are not having savings and in green is when you are having savings. So almost all the time, if you can change, you are having savings. Maybe the biggest difference is in Spain. But as I know, what's the situation in Spain better than in other places? I know that in Spain, you already have bonifications. You have less taxes. They are going to start having CO2, let's say, reducing prices if they save a lot. And they are, and you also have free parking. So at the end, that will probably end up in savings. The second part is Mexico. They have a very big percentage. But right now, we feel like they don't have as wide as they offer us we have in Europe or in North America for electric vehicles. So that's not possible yet for them to change all that vehicles. And for example, the third highlight is if you see in the United States is a white country. So normally, vehicles do long distances. So you cannot really expect to have a big percentage of battery electric vehicles already. But if we look at New York, that normally small vehicles in New York, they work inside Manhattan and they only work in Manhattan. And they communicate with the outside, with other big trucks or other vehicles through the warehouse. So you can see how the percentage is much bigger in New York. This is because the distances, mainly, then you have all the economic calculations. But I took a look also at the distances. So we have here the median of the average distances per day per country. And also, I took a look at the maximum distance. And I calculated the median. So for every vehicle, the maximum distance of all the 18 months, and then I got the median for that. So we can see that the average distance is almost all the time below 200 kilometers. So right now, we have a lot of battery electric vehicles that can do that job today in one day without having to stop in the middle of the day to charge. And the maximum distances, the worst case is a little bit above 600 kilometers. But now we have also some battery electric vehicles that could do that only charging one time in the day. So I also decided to take a look by country to the Plaginibrid electric vehicle readiness bike country. So again, only 20% of the days you are using the combustion engine. Every other day, you can do it full electric without having to stop to charge. So you can see the percentage is very low, the one in green. In blue, I have when I'm having savings, I'm not meeting that 20% of the days. But you can see almost all the time you are having savings in a long life of the vehicle because of the difference in the cost. But I decided to look just using the combustion engine a little bit more, so 40% of the days. And you can see already how the percentage starts to grow. One of the key things here is the CO2 emissions as you can expect. So I don't know if you know this part, but burning one liter of gasoline, it's producing 2.3 kilograms of CO2. That's the estimate you have everywhere. The major counterargument for this is saying that producing energy also produce CO2. So that's true, but I'm not counting neither the CO2 that you get when you get to the foil, you extract all the foil, you filter it, and you transport it to everywhere. That's also producing a lot of CO2 that I'm not counting here. So that's just 2.3 kilograms. So with this, I decided to take a look again by country and by city at how much CO2 you could save in all the life of a vehicle if you change an internal combustion engine vehicle for a battery electric vehicle. See some countries or some cities, you can see they are above 50 tons of CO2 at the life of the vehicle. That's the average per vehicle. There is an interesting point here also that you can see United States and Canada, they have much, the bar is much bigger, that's because they normally use bigger cars, they have pickups, the foil price is so low, they are not very concerned on pollutants, we are here, are not so in a space to park the cars. But that's a lot of CO2 you could save. I also did a little bit of analysis on savings. So how much you could save at the end of the life of the car with the difference in prices, the maintenance, just using, this case is only using the car without charging it midday. So that's also generating more savings. So after the seven years or 200,000 kilometers, you can get around 10 or $20,000 in savings. Also took a look, just looking at the usage of the last 18 months, how much you could get and my average was around 2000 USD dollars. That's for the vehicles I actually analyzed on the last, on the past time. Just because they are delivery vehicles, they are burning a lot of fuel, so if they are burning energy instead of fuel, the price is much cheaper, so they could save a lot. And of course the environmental savings, that's around 47 CO2 tons per vehicle in my analysis. If you change the internal combustion engine to a battery electric vehicle, that's very high. And it's also, now we are going to start having taxes reducing if you are reducing CO2. So that's a big important part in savings. So here I have London again, I have it for a reason. So I had a curious number in savings in United Kingdom, so I got a negative number in savings. So I got, you were losing 800 dollars going electric that maybe with the bonifications, you're already covering it, but it was the only place where I got getting a negative number. So I look a little bit into it, and I don't know if you know that, but in London, now to access the center of the city, you have to pay 12.5 pounds every day. Every day you get inside, you pay 12.5 pounds. So if the vehicles that have negative savings go into London, if they are battery electric vehicles, they will, it's free for them. So the savings will go for a negative number minus 800 to a positive 1.6 thousand, few USD dollars. So we have talked about the pollution, how bad it is. We have talked about how geotab treats data, how changing electrification, a big number of commercial vehicles can do a huge positive impact here. And how in geotab we really know those commercial vehicles. We know how they work, we know how we can use them. So we can try to help there. Now I decided to take a look also at the last part, like what's the major stopper for this? What do people think of electric vehicle? Why they don't think about it more when changing a vehicle? So one important part is they don't have real knowledge of how they use the vehicles. Like you really need telematics to go electric. You need to know how much distance you are doing every day, need to know every day you are going to fit the distance you will have from the battery electric vehicles. You need to know exactly how much fuel you are burning, if that's going to be savings for you or not. We don't want you to change the vehicle if you are not going to get any savings there. We want you to get savings and be more environmental friendly, let's see. So the major stoppers just recently, PONS that is an organization, launches a study where they asked Spanish people what do they think about electric vehicle? So they did two parts. The first is with fleet managers. So they asked fleet managers, most of them the biggest percentage agreed that the main topic now in mobility is electric vehicle. And the stops for them were charging points, price and range that I think you can expect those. And like right now they only have 2% of battery electric vehicles and 2% of plug-in hybrid electric vehicles. The next part is the private owners. So they asked also to the private owners, what do they think? And only 10% of them are thinking in electric vehicles as real possibility. I think again the charging points is the major stopper. In the survey they said so, also the range and the price. They think they are going to lose money, they think they can't fit the range. And of that I kind of think so we don't have yet enough charging points to have a massive number of electric vehicles in any city. So actually in this one I checked the results I got from my own vehicle. So I did the analysis in all the vehicles and I have a device in my vehicle and I got the results. Actually I was happy I couldn't make to buy an electric vehicle because I just bought a year ago my car. But I got that 92% of the days I could have been able to do all my distance with the worst case of one battery electric vehicle. Maybe with better infrastructure, better charging points I could have been able to have a battery electric vehicle instead of a combustion engine. So here I have some conclusions, just the five major points. So the first one is air quality is below healthy standards. And that's true, I think you can feel it. You have seen pictures of Asia and China. That's very bad, you cannot do any sport outside there. It's very bad for the health. It's not only the deaths it's causing, it's also the problems it's generating to new sickness, new problems to the people. So if all the cities are focusing right now on taking measures against traffic that's because it's a major part of this. So the pollution, there are other sources of pollution that I know less about them but the cars are a big part of it. So electrification, a huge amount of vehicles can have a huge positive impact in air quality. And also in climate change and health at the end. So the concers, that's the major stopper for this happening is electrification, a range, price and charging points. Think you probably all thought that before. I thought that before. Now with the Serbia, I checked that a lot of people is thinking the same. But in our analysis, 10% of internal combustion engine vehicles looking at 1.2 million vehicles around the world can go electric now. Today they could change tomorrow, they could sell the old vehicle and buy an electric vehicle and it could do the job and they will make them savings. And the last one is maybe it's not for you yet like in my case, I couldn't do the range yet but I think it's coming and it will be. All the cities are pushing for that. I checked also the price of the kilowatt hour in batteries. It dropped 10 times since 2010 to 2018. And I checked also for just to put an example, the Nissan Leaf that was one of the best electric vehicles 10 years ago, the one of the first ones. The range was only 120 kilometers and it took more than eight hours to charge it completely. Today the range of Nissan Leaf is 360 kilometers and they have the rapid charge. So that's much better. So also with all that and the actions the governments are taking, I think it will come. All the people in the fleet management area are thinking on electric vehicle and they are trying to see if they can go electric but the major stopper again is they don't really know how they use their vehicles so they cannot be sure. They may end up losing a lot of money. They may end up not changing enough vehicles but they with this kind of analysis and probably in the future that will be much easier and we could go active. I think that's all I tried to keep it short because we were just before two. So if you have any questions now you can ask me here or I will be around after and we have a booth at the end in the left that you can go visit us. Thank you Jorge. Any questions for Jorge? Go ahead here. Thanks for your talk. It was really interesting. There is one question that they have regarding the electric vehicle. So have you studied what could happen if 10% of 15% of the fleet change from one day to another to electric? What will happen with the energy generation and how much pollution will be generated by the current way we generate electricity? And if it will be able to be managed by green energy or we will need to waste more petrol, more nuclear and more other kind of non-clean energy. Thanks. That's a very good question, thanks. So one of the things we are supposing is that you can charge the vehicle at night. So this is mainly for fleets. Maybe if you have a house or you have a parking you can do the same. But the idea is they can have their or charging points at their base. So they can charge the cars there. So they really have to think how much vehicles they are going to change and prepare the warehouse for that. In energy, now I think most of the companies, the energy companies are jumping in that and offering alternative plans so they don't get low in energy or they don't have any problem when charging the vehicles. And at the end the contamination producing energy that's a very interesting one. We are analyzing that part of, we have checked how, you probably all know it, but how renewable energies are growing right now. They are producing a lot of energies in some countries. Thanks to them they are having like negative cost of energy thanks to renewable energies. So maybe as you say, still we are making some pollution by producing energy. Still it's less than all the pollution you will make with an internal combustion engine vehicle preparing all the fuel and burning it in the engine. Also the engines at the end like all the filters they have that pollutes a lot at the end of the life of the vehicle. And also with the growth we are having and we think we will, it's going to be for sure more savings with an electric vehicle than with, in CO2, than with an internal combustion engine. Great, any more questions? One more here. Thanks for the talk first of all. I have a question about if profiles were taken into account, I mean for example, I guess the driving pattern of a taxi is very different from somebody who was to work and doesn't have to stop can get in a different highway. Yeah. Okay. So we have right now one of the most important machine learning projects we are doing is the vocation prediction. So we like for privacy we don't get into the details of the customer. We work all the time with aggregated anonymous data so we cannot really get into the details we don't want to but we can analyze how the vehicle works. So we can, for example, just by the hours you can differentiate some of the vehicles like if they have one peak hour in the morning, one in the afternoon, sometimes midday, that's probably an office vehicle. If they have in the morning, in the afternoon but wider range, a lot of smaller stops, small distances, it can be a school bus or a school vehicle and a delivery vehicle you will see like all the day filled, like from nine to five, nine to nine all filled with movement. So that's taking into account the type of vehicle. There are some type of fleets that they have better chances of being successful going electric, they're one that less but at the end is more on the main thing, the main concept for everyone is the range and the charging points. So the main thing right now is the distance, the daily distance. If we look at the last three months or the last 18 months and every single day you are below the worst case that's being very cautious actually, you can probably go electric without having any worry on if you will make the distance or not. Independently on the type of vehicle. The stops, the starting and stop the engine doesn't affect so much an electric vehicle as it can affect an combustion. Great, thank you. Any more questions? If that's not the case, then thank you to Jorge, another round of applause. And our next talk will begin in about eight minutes.