One of the main reasons I was interested in getting my master’s in the Intelligent Transport Systems & Logistics program at Linköping University, was because of the serious emphasis this program places on the future developments of transportation technology and city infrastructure. Before applying at LiU, I did various grad school tours at different universities in the US and applied to multiple universities in Europe, but the curriculum in each of these programs were failing to prepare transportation planners for a future in which automation, connectivity, and technology lead the way.
Regarding Transportation Systems Engineering, the differences between LiU and these other universities were quite clear. This program not only provides an understanding of more traditional traffic planning, it also incorporates elements that are largely focused on the integration of IT and telecommunications into how transport and logistic systems will operate in the future. The focus on this within my program is what solidified my decision in coming here.
Within the curriculum, you can find an array of different topics that would normally be left out of a more traditional transportation systems engineering master’s, such as Smart Cities, Internet of Things, and Mobile Communications & Networks, to name a few.
This period in particular, I have been working a lot within my Smart Cities course. This course provides lectures with more general project ideation activities and technical seminars on sensors, but the main focus has been regarding the project work. In the labs, our projects utilize software such as Java, SQL, and QGIS, to experiment in different ways with the collection of sensor data to develop applications that can be utilized by citizens in a hypothetical “smart city”.
One project that I found especially interesting so far is this geofencing lab (seen in the image above) we have been working with over the past week. The idea of this project is to design a frontend application for an android phone in java that is able to collect GPS data, and then send this data to a database via a backend application, where it is manipulated and plotted on a graph. Within the backend application, the main objective of the project was to determine if a user of the mobile device was within a certain distance of an established geofenced area, in this case the bus stops on Kungsgatan in Norrköping. In a smart city, this triggering of a geofenced area could prompt a specific action to take place on a device that could give useful information to a nearby user.
Someone who see this and is interested in the program might look at this and think – omg, I do not know how to program in Software X … or work with Software Y. But this is okay!
The first semester of the program students are exposed to general programming logic in MATLAB and other content with GIS. For this course specifically, we operate in Java which I just started learning (through self-study) this past February! The takeaway of this course is to understand how device sensors can be utilized to collect data, store this data in a database, and then process this data into a usable application. Being a naturally great programmer in this program is just a plus ;), you will do great if you are curious, want to learn, and work hard!
Where else could studying transportation be so exciting? See you in the courses next year 🙂