Mobility Anomaly Detection is a computational method that identifies deviations from established patterns in the movement behaviors of individuals or entities by analyzing spatiotemporal trajectories within a mobility system.
111
Publications
5.3K
Citations
415
Authors
200
Institutions
Publications per year
2017–2026
44
Parents
Publications
111
Vehicular Social Networks: Enabling Smart Mobility
Zhaolong Ning, Noor Ullah, Xiangjie Kong et al. · IEEE Communications Magazine · 2017 · 337 citations
Trace analysis and mining for smart cities: issues, methods, and applications
Gang Pan, Guande Qi, Wangsheng Zhang et al. · IEEE Communications Magazine · 2013 · 207 citations
1–5 of 111
Authors
415
- BS
3
h-index
- KT
3
h-index
- HX
3
h-index
- YZ
3
h-index
- YS
2
h-index
1–5 of 415
Institutions
200
Shanghai Jiao Tong University
Shanghai, China
5 h-index
17 publications
580 citations
The University of Tokyo
Tokyo, Japan
4 h-index
7 publications
167 citations
Shenzhen Institutes of Advanced Technology
Shenzhen, China
4 h-index
11 publications
1.3K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
4 h-index
8 publications
361 citations
Zhejiang University
Hangzhou, China
3 h-index
6 publications
1.1K citations
Lamar University
Beaumont, United States
3 h-index
3 publications
138 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
4 publications
164 citations
Beijing Jiaotong University
Beijing, China
3 h-index
9 publications
335 citations
1–8 of 200
Venues
- IEEE Transactions on Intelligent Transportation Systems
4 publications · 463 citations
4
h-index
- Pervasive and Mobile Computing
3 publications · 97 citations
3
h-index
- IEEE Transactions on Vehicular Technology
3 publications · 221 citations
3
h-index
- Transportation Research Part C Emerging Technologies
3 publications · 744 citations
3
h-index
- ISPRS International Journal of Geo-Information
IJGI · 3 publications · 60 citations
3
h-index
1–5