So, in summary, there's massive, just absolutely massive opportunity. I'm sure there's much more than I discovered on my survey to put this material together for this week. As hardware design, as I mentioned, sensor and actuator controllers, gateways and interfaces to corporate enterprise platforms like IBM and Amazon Web Services, and these other ones that we've talked about, it can be wired or wireless systems, either way. We saw when Trimble was here, they use the can automotive on the vehicle communication and Ethernet depending on the speed and the bandwidth requirements. Connected cars are really psyched about this. I've mentioned it before, and I think connected cars is part are the key to fully autonomous vehicles because of the cars, I believe, each car needs to be aware of electronically in communication with all the cars around it. When accidents happen and especially when unexpected things happen, people cross the street, people cross the road, animals cross the road, and whenever driven up to Elsers park and seen an elk standing on side of the road, not want, to hit an elk in your car. Easily come right through the windshield and kill you. So, these systems need to be able to identify those objects and those animals, and so forth. These unexpected things. But when all the cars are connected, if an animal leaps in front of a car, a car can hit the breaks and it can be communicating back to a previous cars and slow the car down, so, we don't have these 50 car pile ups like we see periodically when something happens and all these cars smash and vehicle smash into each other. Global navigation satellite systems, a lot of hardware that needs to be designed there. That was interesting on the ones that the Trimble machines that rotate. They decided to deploy two GPS receivers to get finer resolution and know exactly where the bucket is. Then software design. I could probably go on and on here, but all these control systems need algorithms designed and programmed, coded, tested, all of that. Huge opportunities here. Machine Learning and data analytics on the consumption of all of that data from the sensors generating models, playing what-if scenarios trying to increase operational efficiency, reduce cost, increase revenue. Theme of the semester. That is what I have for deeper look into automotive and transportation. Encourage you to take a look at those four PDFs, and take them with you and read them this summer. There's some interesting stuff in there. I did highlight some texts in some of those articles, things that just jumped out at me as important. You may want to be aware of sometime in the future.