 Okay. All right. I guess we can go ahead and start. All right. So thanks everyone for staying here this late for the lighting talks. So I'll talk about a new project that we're starting called pivot and this is a project to collect data from vehicles. So in vehicle data, mostly. And you might be asking yourselves, you know, what are, why do we need in vehicle data? What are the uses? What are the applications? You know, what we can do with it? And let me try to motivate this with a little video. And this is one example as to why you might want to collect in vehicle data. I'm going to get it to start. That's too bad. I was hoping to show this up. Okay. I guess we're going to have to skip this. Sorry about that. So what the video was, and I thought it was going to be interesting to you guys, it was a video showing a test crash. So it was a video that was showing a car being pulled into a truck and then another truck behind it coming in and essentially smashing the car in between two trucks. And the reason that video was done, that experiment was done, was to collect data from black boxes inside cars to collect information about crashes, right? So it was there to collect, to see what information is in black boxes so you can recreate a crash and study a crash and draw conclusions. So that's just one example as to why we may want to collect in vehicle data. There's many more other applications that will have us collect that type of data. So the data, they're needed by researchers who are trying to advance the state of the art, but currently these type of data in vehicle data are very ad hoc. So people collect them to run their experiments. They save them somewhere that don't necessarily get published to the rest of the world. The researchers do their experiments and then the data is left there to language and other people don't get to use it. So this project among others is there to collect the data that other people have produced and make it available to researchers in addition to the data that we collect. So let's see what else. Potential applications. There are applications in the many different types in many different areas that this data can be used for vehicle applications. You can use this data to do system monitoring in the car and optimization. You can collect data from in vehicle infotainment. You can do predictive maintenance and a lot of companies out there already do that. They collect data from your car and then they might send you an email saying your battery is about to die or your engine is having a problem. According to our data, you might want to make an appointment with a repair shop. Other applications include route and trip planning and also information from ADAS from connected vehicles, electric vehicles and so forth. At a higher level, these data can be used by transportation and fleet management to work on passenger safety, traffic management, do ride sharing applications and multimodal mobility where you combine cars and scooters and so forth. And even by insurance. Insurance is actually one of the major entities that require this data and they want it so they can create a new insurance model. Things like pay as you drive, pay you while you drive and so forth. The data may be used by smart cities to do infrastructure monitoring, to do weather sensing, to do asset management and so forth. But also it can be used for safety and cyber security. One example that a lot of companies out there are doing is intrusion detection systems in cars by monitoring the voltages inside a canvas. And this allows them to detect whether a new device has been inserted in a can that perhaps was not authorized to be there. So what is this project? So this project is an effort between the University of Memphis where I am, Colorado State University where Jeremy Daley is one of my co-PIs. And also the USC of the University of Southern California Information Sciences Institute where David Balanson is with Wes Hatterger. The other collaborator in this project is the company, Geotub. And what Geotub does is a telematics company. They're based in Canada, but they're pretty much international. And they have agreed to work with us on this project and they provide some of the data that they collect and make it available to fleet managers. So it's aggregated data so it's anonymized, but it's data from a lot of cars that through this project can be made available to researchers. It's a three-year project started in October and since September 2025, it's about $1.8 million. And the purpose of the project is to support the NSF community or the National Science Foundation community in the U.S. But this is just, this is not exactly true. The NSF will be more than happy if we support the international community with this project. How do you build a project like that? Well, we believe that you need five pillars to build this project. You need your platform, your web server that supports all the user accounts when users can be looking for data and so forth or searching for data and so forth. We need another pillar, which is the collection and curation of the data that we are going to make available to researchers. We need services for researchers for sharing, securing and evaluating data sets. We need tools that researchers can use to manipulate the data and we need community outreach. So this is community outreach is a very important part of this project. And what we're trying to do here is advertise the fact that this infrastructure is there and engage with the community to see what they want, what kind of tools, what kind of services, what kind of data they would like to have. So this is a project that is very feedback oriented. So we work with the community and we try to respond to needs from the community. So going into the five pillars in a little more detail, the pivot platform, it's nothing that you do not expect. So we will have our web server. We will have the, will include security obviously because some of the data we collect is sensitive. It will be hosted on our machines in Memphis and it will get mirrored in Colorado. So this is your standard web service platform with the software needed to do the social interaction user accounts and so forth. The services we plan to deploy are access to data sets and tools for all researchers for data sets that are external. In other words, data sets that we do not collect, we will provide links. We will provide access to the geotab data sets, the data that they provide. We will also provide data from another project called Spindle. I'll talk about it in just a second. And we will also provide data sets that will be crowdsourced through devices that we will distribute. I'll talk about that in just a second too. We will also provide privacy support. So for data that we collect through crowdsourcing, there will be nobs, privacy nobs, that the contributors will be able to turn to decide what level of privacy they're willing to include in the data. We will also provide something called institutional review boards support. Now the IRBs are something that all U.S. universities have, and I suspect other universities in the rest of the world. And what these review boards do is whenever you do research that may involve human subjects, you talk to them, describe what the research is, and then you get approval from them that, yes, it's okay to do the research or no, you have to do this to protect your human subjects. It's a very tricky area. It's sometimes hard and not very easy for researchers to navigate. So we will engage with our IRB and share experiences with other universities who may want to do the same thing. And then we'll provide community coordination and interaction. Now, what data sets are we going to provide? So those are divided into three broad categories. The first one is pretty obvious, is data sets that are out there but researchers at large may not know about. So we will go out, find them, review them and bring them in if we need to, and make the community aware that these data sets have been produced, they have been used to write papers, they have been used to do research, and here's a description of what they are and then you decide whether you want to use it. So that's the easy part. The next category is data from GOTAP, the company, and this is data that GOTAP will provide to us. As I mentioned earlier, this is aggregated data from their devices. We will also provide data from GOTAP, but this is from a program that we run. So in other words, we have a set of a small number of volunteers who have installed devices, telematics devices in their cars, and that data, we don't have restrictions in terms of what we make available. Because it's coming from volunteers, that data is fully available to us and we are free to distribute it according to what the small group of volunteers are designed. And finally, the other type of data is through hand-lockers, devices that we are implementing and we will distribute to the community, and this is data from cars and trucks. So a little more detail on community data sets. Again, this is data that's out there. A few examples are listed here. If you haven't heard of these data sets and if you're looking for data sets and you haven't seen these, then that's why we are here to find them for you. The GOTAP telematics data, it's coming from a service that GOTAP provides called Altitude. This is data from all the cars that they serve, about two and a half million cars around the world. And it's aggregated data, and we are going to get two main data sets from them. One is called Intersection, so this is data about intersections. How long does it take to go through an intersection, what's the average speed, and so forth. And the other data set is called Roads, and this is characteristics about roads in general, about mobility and about data that allows you to do individual road analysis. So the advantage of the data from GOTAP is that while it's anonymized and aggregated, it's coming from a lot of cars, millions of cars. On the other end of the spectrum, again with GOTAP's help, we run a small program that we call Spindle, and essentially what this program is, is a few of us installing GOTAP devices in our cars and that day using GOTAP's cloud infrastructure to collect that data, but then we go to the cloud and collect that data for us. Okay, alright, I'll be done in just a second. Alright, here's an example of the data we collect from Spindle. Here's a map of me going to the airport and then engine information. This is a picture of the camp logger, so we are planning to implement and install in the cars. And this is an example of data that we will be collecting through camp loggers, and this is a knowledge pyramid, and we go from very low level data and then building on top of it up to high level data. This is the type of outreach that we will do, it's what you expect, webinars and educational events and so forth. Let me not go through the benefits of Pivot, hopefully you'll see these, but very quickly these are the benefits that we expect for the AGL community and then benefits for the NSF researchers on our side. We think there's benefits on both sides. Alright, and these are the usual suspects, and there's a website that you can go to and start getting information and very soon you'll be seeing data on that website, but feel free to use these links to send us email and engage in whatever capacity you want. So I was under the impression that I had 20 minutes and that you're stopping me at 10. Anyway, so sorry for the rush at the end. Any questions, anything that I can answer? So again, to recap, this is a project to collect in-vehicle data and make it available to the community along with all the services and the community outreach to go with them with the purpose of fostering research, developing applications and essentially giving you the data so you can come up with whatever research or ideas for applications that you may have. And we will happily take any data that you have created if you create a data but you don't want to go through the trouble of advertising, distributing it, then we'll happily take the data from you and do the advertisement for you if you want to give that data to the community. Okay, alright. If there's any noble questions, thank you.