The study of sociology and intrinsic human characteristics is reaching new frontiers after getting the access of mobile data sources. They act as a promising source for research in various fields, such as criminology, mobility, disaster management, etc., due to their event-based nature. Despite potential links between mobile datasets and human social behaviors, the research in this domain is limited due to the unavailability of real mobile data. Henceforth, we present a first-in-literature data source, with real spatiotemporal time series for the 68 most used applications in different French metropolitan areas. The data source acts as an ideal solution to the missing puzzle for solving many problems, such as mobility planning, tourist and migrant flows, urban structures and interactions, event detection, and, urban well-being.
Sachit Mishra received his bachelor’s in Electronics and Communication from Jaypee University of Engineering and technology, Guna, India and his M.Sc degree in Computer Science from the Politecnico di Torino, Torino, Italy. He is currently pursuing his Ph.D. degree with the Network Data Science Group at IMDEA Networks, Madrid, Spain. During his master’s thesis, he collaborated with Tierra Telematics, developing a machine learning application which enabled the automatic scheduling of the periodic maintenance of industrial vehicles. His main research interests are machine learning, Big Data, data science, data analysis, and remote sensing.
This event will be conducted in English