Have you ever had problems connecting to the Internet with your smartphone due to a weak or non-existing WiFi signal? What if you could see those wireless signals in the environment and utilise them, e.g., to find a more beneficial spot for either your phone or conversely the wireless router to provide a better signal coverage? Now think about the Internet of Things made of billions of wireless devices, whose functionality depends on wireless connectivity. This project group targets the visualisation of wireless waves emitted by IoT devices as if they were visible light ones, with the goal of supporting users in planning functional IoT systems.
After a series of lectures discussing the behaviour of wireless signals in real environment and tutorials in which the wireless modelling engine developed in prior research work will be introduced, the participants will present specific techniques of relevance for the project. In particular, the attendees will learn about how wireless signals propagate in an environment with obstacles as well as how 3D visualisation engines can be exploited to represent such information. Depending on the number of students, we will also explore the techniques that will allow to operate such visualisation on a smartphone and navigate in the wireless environment while the user moves around.
Afterwards, the participants will design, implement and experiment with a practical system in which the acquired knowledge will be exploited to prototype a visualisation engine able to represent the wireless signals in real-world scenarios.
This project group is only suitable for AI-SE master students and it will be taught in English. The number of participants in this course ranges between 6 and 10. The admission to this course is managed centrally.
If you have questions or if you want to participate in the project, please send an email to email@example.com.
More information is available on the moodle page of the course which is available here.
Entry in LSF: Project Group
The first meeting for this project will take place on Thursday, 18.04.2019 at 11.00h in Room S-A 126.