Context
It is important to know where wifi hotspots for indoor localization. Using Received Signal Strength Indication (RSSI) and distance of a person to a wifi spot, we can roughly find wifi spots in an area. What if we did not have RSSI information?
Objective
This project aims to estimate wifi spots using users’ location and wifi scans. We focus our research on the Breadcrumbs dataset (it is mandatory to work on this dataset) and Eduroam public wifi dataset [4]. We plan a three-step plan for this project as follows:
Step 1: Students must implement the algorithm proposed by Kulkarni et al. in [1] to find wifi hotspots geofences.
Step 2: Using users’ location and minimum and maximum range of provided wifi connections, students should calculate and estimate where wifi connections are located.
Step 3: Evaluate your approach using the Eduroam public wifi dataset in Lausanne, Switzerland [4]. We will try to provide you with the list of other public wifi locations.
This subject as a Master’s Thesis requires you to read research papers on your project idea and take the lead in your Master’s Thesis.
If you want to learn more about the Breadcrumbs Dataset, we suggest you read the Breadcrumbs Paper [1] and Breadcrumbs Dataset Description [2].
Extend This Subject to A Master’s Thesis
If you want to work on this subject as a Master’s Thesis, we expect you to read research papers, and come up with research questions.
Prerequisites
Students must be confident with their algorithms, mathematics, programming, data science, and machine learning skills. Preferred programming languages are Java and Python.
References
[1] Vaibhav Kulkarni, Arielle Moro, Bertil Chapuis, and Benoît Garbinato. 2017. Extracting Hotspots without A-priori by Enabling Signal Processing over Geospatial Data. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’17). Association for Computing Machinery, New York, NY, USA, Article 79, 1–4. DOI:https://doi.org/10.1145/3139958.3140002
[2] Breadcrumbs Dataset Description, https://github.com/doplab/breadcrumbsDB/blob/main/Breadcrumbs_Dataset_Description.pdf
[3] Vaibhav Kulkarni, Arielle Moro, Bertil Chapuis, and Benoît Garbinato. 2017. Extracting Hotspots without A-priori by Enabling Signal Processing over Geospatial Data. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’17). Association for Computing Machinery, New York, NY, USA, Article 79, 1–4. DOI:https://doi.org/10.1145/3139958.3140002
[4] List of Public Eduroam Wifis in Switzerland, https://monitor.eduroam.org/kml/ch.kml