The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to
rethink the way smart cities infrastructures are designed and managed, and solve a number …

Human social interactions occur in group settings of varying sizes and locations, depending
on the type of social activity. The ability to distinguish group formations based on their …

Abstract In the United States, the buildings sector consumes about 76% of electricity use and
40% of all primary energy use and associated greenhouse gas emissions. Occupant …

Abstract Multistep Human Density Prediction (MHDP) is an emerging challenge in urban
mobility with lots of applications in several domains such as Smart Cities, Edge Computing …

Sanitizing railway stations is a relevant issue, primarily due to the recent evolution of the
Covid-19 pandemic. In this work, we propose a multi-robot approach to sanitize railway …

Background: The COVID-19 pandemic necessitated public health policies to limit human
mobility and curb infection spread. Human mobility, which is often underestimated, plays a …

Accurate and interpretable prediction of crowd flow would benefit business management
and public security. The existing studies are challenged to adapt to the indoor environment …

The tremendous CoVid-19 outbreak has had a significant impact on the lives of people
anywhere in the world. Several approaches have been presented with the aim of helping in …

This work introduces an alternative solution to costly conventional approaches for large-
scale travel behavior data collection by utilizing an opportunistic sensing data source ie, Wi …

Crowd flow prediction plays a vital role in modern city management and public safety
prewarning. However, the existing approaches related to this topic mostly focus on single …