The Breadcrumbs is a mobility dataset. It was collected in 2018 around the University of Lausanne and EPFL by DOPLab and Information Security and Privacy Lab. The dataset consists of 80 people’s data through sensors on their devices, e.g., Bluetooth, WiFi, and GPS. Moreover, the Breadcrumbs dataset stands out as having ground-truth data of point-of-interest (including semantic labels), demographic attributes, contact records, calendar events, lifestyle information, and social relationship labels between the participants of the study. 

If you choose to work on this subject, you will analyze the dataset to answer research questions (to be discussed further and in detail). We propose some projects on our website: Estimating FriendshipEstimating WiFi Spots, and Estimating Public POI. However, if you have another idea that you want to work on, do not hesitate to contact us.

If you want to learn more about the Breadcrumbs Dataset, we suggest you read the Breadcrumbs Paper [1] and Breadcrumbs Dataset Description [2].

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

Contact

melike.gecer@unil.ch