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Grant: Discovery Grants Program - Individual

Wilfrid Laurier University

$23,000.00

Mining Urban Trajectories

EF 2018-19

Résumé
Advances in modern sensing technologies and large scale computing infrastructures have generated a huge amount of trajectory data. These urban trajectory data contain rich information of moving objects including people, vehicle, etc., and foster a wide variety of applications, such as road network reconstruction, intelligent traffic management, and air quality control. While governments, industrial companies, and organizations have realized the tremendous potential of these data, their complex nature presents unique challenges that cannot be easily solved.*The objective of the proposed research program is to address the challenges arising from mining urban trajectory data, and provides answers to the following three research questions: How to understand objects' mobility patterns from their trajectories? How to fuse the heterogeneous trajectories, and solve the data sparsity problem? How to detect anomalies from urban trajectories?*The results of this research will advance the state-of-the-art technique in trajectory data mining, providing new insights on understanding people's moving behaviors from various perspectives. Besides, it will bring significant benefit to different parties, including governments, businesses, and end users, through a series of new applications and services enabled by the research results.
Programme
Discovery Grants Program - Individual
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2018-06641
Name nom
Liu, Yang
Department département
Physics and Computer Science
Organization id
35
Institution établissement
Wilfrid Laurier University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
23000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information technology
Research subject fr
Technologie de l'information
Partie
1
Nb partie
5
Application title
Mining Urban Trajectories
Keyword
NSERC
Application summary
Advances in modern sensing technologies and large scale computing infrastructures have generated a huge amount of trajectory data. These urban trajectory data contain rich information of moving objects including people, vehicle, etc., and foster a wide variety of applications, such as road network reconstruction, intelligent traffic management, and air quality control. While governments, industrial companies, and organizations have realized the tremendous potential of these data, their complex nature presents unique challenges that cannot be easily solved.*The objective of the proposed research program is to address the challenges arising from mining urban trajectory data, and provides answers to the following three research questions: How to understand objects' mobility patterns from their trajectories? How to fuse the heterogeneous trajectories, and solve the data sparsity problem? How to detect anomalies from urban trajectories?*The results of this research will advance the state-of-the-art technique in trajectory data mining, providing new insights on understanding people's moving behaviors from various perspectives. Besides, it will bring significant benefit to different parties, including governments, businesses, and end users, through a series of new applications and services enabled by the research results.