scholarly journals A Survey on Trajectory Data Mining: Techniques and Applications

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 2056-2067 ◽  
Author(s):  
Zhenni Feng ◽  
Yanmin Zhu
Keyword(s):  
Data Mining ◽  
Trajectory Data ◽  
Data Mining Techniques ◽  
Trajectory Data Mining

scholarly journals Handover detection approach based on trajectory data mining techniques

2018 ◽  
Vol 2018 (16) ◽  
pp. 1534-1537 ◽  
Author(s):  
Nan Han ◽  
Shaojie Qiao ◽  
Dunhu Liu ◽  
Peng Ding ◽  
Yongqing Zhang ◽  
...  
Keyword(s):  
Data Mining ◽  
Trajectory Data ◽  
Data Mining Techniques ◽  
Detection Approach ◽  
Trajectory Data Mining

Telemetry Data Mining Techniques, Applications, and Challenges

2017 ◽  
pp. 915-924
Author(s):  
Sara Ahmed ◽  
Tarek Gaber ◽  
Aboul Ella Hassanien
Keyword(s):  
Data Mining ◽  
Large Scale ◽  
Moving Objects ◽  
Radio Telemetry ◽  
Wide Spectrum ◽  
Movement Behavior ◽  
Trajectory Data ◽  
Data Mining Techniques ◽  
Trajectory Data Mining ◽  
The 1960S

The most recent rise of telemetry is around the use of Radio-telemetry technology for tracking the traces of moving objects. Initially, the radio telemetry was first used in the 1960s for studying the behavior and ecology of wild animals. Nowadays, there's a wide spectrum application of can benefits from radio telemetry technology with tracking methods, such as path discovery, location prediction, movement behavior analysis, and so on. Accordingly, rapid advance of telemetry tracking system boosts the generation of large-scale trajectory data of tracking traces of moving objects. In this study, we survey various applications of trajectory data mining and review an extensive collection of existing trajectory data mining techniques to be used as a guideline for designing future trajectory data mining solutions.

The discovery of personally semantic places based on trajectory data mining

2016 ◽  
Vol 173 ◽  
pp. 1142-1153 ◽  
Author(s):  
Mingqi Lv ◽  
Ling Chen ◽  
Zhenxing Xu ◽  
Yinglong Li ◽  
Gencai Chen
Keyword(s):  
Data Mining ◽  
Trajectory Data ◽  
Trajectory Data Mining

scholarly journals Big Trajectory Data Mining: A Survey of Methods, Applications, and Services

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4571
Author(s):  
Di Wang ◽  
Tomio Miwa ◽  
Takayuki Morikawa
Keyword(s):  
Data Mining ◽  
Social Dynamics ◽  
Trajectory Data ◽  
Traffic Dynamics ◽  
Spatiotemporal Information ◽  
Trajectory Mining ◽  
Trajectory Data Mining ◽  
Urban Problems ◽  
Practical Implications ◽  
Wide Usage

The increasingly wide usage of smart infrastructure and location-aware terminals has helped increase the availability of trajectory data with rich spatiotemporal information. The development of data mining and analysis methods has allowed researchers to use these trajectory datasets to identify urban reality (e.g., citizens’ collective behavior) in order to solve urban problems in transportation, environment, public security, etc. However, existing studies in this field have been relatively isolated, and an integrated and comprehensive review is lacking the problems that have been tackled, methods that have been tested, and services that have been generated from existing research. In this paper, we first discuss the relationships among the prevailing trajectory mining methods and then, classify the applications of trajectory data into three major groups: social dynamics, traffic dynamics, and operational dynamics. Finally, we briefly discuss the services that can be developed from studies in this field. Practical implications are also delivered for participants in trajectory data mining. With a focus on relevance and association, our review is aimed at inspiring researchers to identify gaps among tested methods and guiding data analysts and planners to select the most suitable methods for specific problems.

Trajectory data mining: integrating semantics

2013 ◽  
Vol 26 (5) ◽  
pp. 516-535 ◽  
Author(s):  
Ahmed Elragal ◽  
Nada El-Gendy
Keyword(s):  
Data Mining ◽  
Trajectory Data ◽  
Trajectory Data Mining

scholarly journals Trajectory Data Mining in Distributed Sensor Networks

2015 ◽  
Vol 11 (7) ◽  
pp. 913165
Author(s):  
Shaojie Qiao ◽  
Huidong (Warren) Jin ◽  
Yunjun Gao ◽  
Lu-An Tang ◽  
Huanlai Xing
Keyword(s):  
Data Mining ◽  
Sensor Networks ◽  
Trajectory Data ◽  
Distributed Sensor Networks ◽  
Distributed Sensor ◽  
Trajectory Data Mining
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