| Title |
Influential spatial facility prediction over large scale cyber-physical vehicles in smart city |
| ID_Doc |
36647 |
| Authors |
Wang, HT; Li, Q; Yi, F; Li, Z; Sun, LM |
| Title |
Influential spatial facility prediction over large scale cyber-physical vehicles in smart city |
| Year |
2016 |
| Published |
|
| DOI |
10.1186/s13638-016-0606-4 |
| Abstract |
Facilities are critical infrastructures in smart city. Influence of facilities is affected by large-scale moving objects such as people and vehicles. Calculating the influence of facilities is an important task of urban computing, which adopts sensing technology to obtain objects' movement patterns in urban space and applies this information to discover many hidden issues cities face today. In this paper, we propose a computationally efficient grid partition method to compute the influence of facilities in real time, under trajectories of large-scale cyber-physical vehicles. We next predict the influence changes of facilities over dynamic vehicles using trajectory-based Markov model. We conduct evaluation using a real-world dataset, including 1-month taxi trajectories with 27,000 taxis and 1000 facilities. Experimental results shows that our solution is more efficient and achieves an accuracy of 85 %. |
| Author Keywords |
Smart city; Facility influence; Mobility prediction; Cyber-physical vehicle |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000374285400001 |
| WoS Category |
Engineering, Electrical & Electronic; Telecommunications |
| Research Area |
Engineering; Telecommunications |
| PDF |
https://jwcn-eurasipjournals.springeropen.com/track/pdf/10.1186/s13638-016-0606-4
|