Unsupervised inference of significant locations from wifi data for understanding human dynamics

TB Nguyen, T Nguyen, W Luo, S Venkatesh… - Proceedings of the 13th …, 2014 - dl.acm.org
Motion and location activities are essential to understanding human dynamics. This paper
presents a method for discovering significant locations and individuals' daily routines from …

[图书][B] Mobility data

C Renso, S Spaccapietra, E Zimányi - 2013 - books.google.com
Mobility of people and goods is essential in the global economy. The ability to track the
routes and patterns associated with this mobility offers unprecedented opportunities for …

Identifying human spatio-temporal activity patterns from mobile-phone traces

G Di Lorenzo, F Calabrese - 2011 14th International IEEE …, 2011 - ieeexplore.ieee.org
Understanding and modeling people's mobility is a crucial component of transportation
planning and management. Research in this area was originally concentrated on modeling …

Detecting and understanding urban changes through decomposing the numbers of visitors' arrivals using human mobility data

TN Maeda, N Shiode, C Zhong, J Mori, T Sakimoto - Journal of Big Data, 2019 - Springer
In recent years, mobility data from smart cards, mobile phones and sensors have become
increasingly available. However, they often lack some of the key information including the …

Adaptive mobility mapping for people tracking using unlabelled Wi-Fi shotgun reads

M Zhou, AK Wong, Z Tian, VY Zhang… - IEEE …, 2012 - ieeexplore.ieee.org
Mobility tracking plays an important role in identifying human activities and providing
location-based services (LBSs). Up to now, with the help of special infrastructures or …

A mobility analytical framework for big mobile data in densely populated area

Y Qiao, Y Cheng, J Yang, J Liu… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Due to the pervasiveness of mobile devices, a vast amount of geolocated data is generated,
which allows us to gain deep insight into human behavior. Among other data sources, the …

[HTML][HTML] A dynamic mixed logit model with agent effect for pedestrian next location choice using ubiquitous Wi-Fi network data

A Beaulieu, B Farooq - International journal of transportation science and …, 2019 - Elsevier
Large scale automated data collection on the movement and activities of pedestrians is a
challenging problem. In a previous work we developed a network of cheap sensors that can …

Wifi probes sniffing: an artificial intelligence based approach for mac addresses de-randomization

M Uras, R Cossu, E Ferrara, O Bagdasar… - 2020 IEEE 25th …, 2020 - ieeexplore.ieee.org
To improve city services, local administrators need to have a deep understanding of how the
citizens explore the city, use the relevant services, interact and move. This is a challenging …

Inferring stop-locations from wifi

DK Wind, P Sapiezynski, MA Furman, S Lehmann - PloS one, 2016 - journals.plos.org
Human mobility patterns are inherently complex. In terms of understanding these patterns,
the process of converting raw data into series of stop-locations and transitions is an …

Cross-checking different sources of mobility information

M Lenormand, M Picornell, OG Cantú-Ros, A Tugores… - PloS one, 2014 - journals.plos.org
The pervasive use of new mobile devices has allowed a better characterization in space and
time of human concentrations and mobility in general. Besides its theoretical interest …