A vast amount of location information exists in unstructured texts, such as social media
posts, news stories, scientific articles, web pages, travel blogs, and historical archives …

This systematic literature review aims to investigate the current state-of-the-art in machine
learning (ML) based road traffic analysis, hindrance estimation, and predicting vehicle safety …

Traffic accidents are a major concern worldwide, since they have a significant impact on
people's safety, health, and well-being, and thus, they constitute an important field of …

Natural language texts, such as tweets and news, contain a vast amount of geospatial
information, which can be extracted by first recognizing toponyms in texts (toponym …

The practical applications of social media have raised the bar for real-time event detection
all over the globe. It has been deemed useful for extracting important data that enables …

Owning to the massive growth in internet connectivity, smartphone technology, and digital
tools, the use of various online social networks (OSNs) has significantly increased. On the …

Traffic incidents are a problem that affects the entire population in general, causing high
costs for those involved and for the authorities, in countries and third world cities such as …

For a location inference model to be successful, the properties of the geotagged tweets
where the location inference model is developed and those of the non-geotagged tweets …

Abstract In Panama City, Panama, as in many cities, the large number of cars on the roads
and random traffic events produce constant and extensive traffic jams. These issues are …

Road accident detection and prevention is one of the most challenging problems in the
research field revolving around a multitude of problems that need to be addressed. In this …