Participants: Andrew T. Campbell leads the MetroSense project on peoplecentric sensing.
His group developed a number of early sensing systems and applications for sensorenabled …

Modeling human mobility has a wide range of applications from urban planning to
simulations of disease spread. It is well known that humans spend 80% of their time indoors …

This paper presents a novel framework that includes an inhomogeneous (time-variant)
Hidden Markov Model (HMM) and learning from data concepts. The framework either …

Mobile sensing has been gaining ground due to the increasing capabilities of mobile and
personal devices that are carried around by citizens, giving access to a large variety of data …

People-centric sensing using people's smartphones offers new research opportunities for
large case studies. It presents many challenges, eg., efficient capture of person's mobility …

Various studies have investigated the predictability of different aspects of human behavior
such as mobility patterns, social interactions, and shopping and online behaviors. However …

Advances in mobile, wearable and embedded sensing technology have created new
opportunities for research into a variety of health conditions. This has led to the field of …

In recent years, human behavior sensing and understanding attracts a lot of interests due to
various societal needs, including security, natural interfaces, gaming, affective computing …

Collecting and analyzing data from sensors embedded in the context of daily life has been
widely employed for the monitoring of mental health. Variations in parameters such as …