ABSTRACT
Urban computing would be the method of acquiring, integrating, and analyzing large amounts of non-homogeneous information collected in urban areas by a number of sources which include sensing devices, gadgets, automobiles, housing developments, and humans in order to address significant problems such as environmental pollution, steadily increasing energy usage, as well as traffic problems. Urban computing links inconspicuous and ubiquitous sensor technology, powerful data management, and analytics techniques along with visualization methodologies. This allows for the collection of vast volumes of data related to the objects that are moving which called trajectories are providing potentially useful knowledge more about objects moving. Automated methods for understanding this material are known as trajectory data mining The goal of this article is to analyze (1) the way in which trajectory data mining activities are being described at an existential level, (2) the exact sort of knowledge that can be extracted through trajectory data, and (3) the methods that trajectory data mining techniques apply toward various tasks of urban computing.
