TY - GEN
T1 - World expo problem and its mixed integer programming based solution
AU - Xu, Hongteng
AU - Luo, Dixin
AU - Huo, Xiaoming
AU - Yang, Xiaokang
PY - 2013
Y1 - 2013
N2 - In this paper, we introduce an interesting "World Expo problem", which aims to identify and track multiple targets in a sensor network, and propose a solution to this problem based on the mixed integer programming. Compared with traditional tracking problem in the sensor network, the World Expo problem has following two features. Firstly, the target in the network is not limited to single individuals. It can also be a group composed of multiple individuals with same path in the network, which implies that multiple targets can share the same path and be detected by the same sensor at the same time. Moreover, both the size and the number of groups are unknown. Secondly, differing from traditional sensor networks, the sensor network in the World Expo problem usually is sparse. These two features increase the difficulty in identification and tracking. To solve the aforementioned problem, we analyze the solvability of this problem and come up with a mixed integer programming based algorithm. The simulation result shows that our method has good performances and is robust to errors in the data.
AB - In this paper, we introduce an interesting "World Expo problem", which aims to identify and track multiple targets in a sensor network, and propose a solution to this problem based on the mixed integer programming. Compared with traditional tracking problem in the sensor network, the World Expo problem has following two features. Firstly, the target in the network is not limited to single individuals. It can also be a group composed of multiple individuals with same path in the network, which implies that multiple targets can share the same path and be detected by the same sensor at the same time. Moreover, both the size and the number of groups are unknown. Secondly, differing from traditional sensor networks, the sensor network in the World Expo problem usually is sparse. These two features increase the difficulty in identification and tracking. To solve the aforementioned problem, we analyze the solvability of this problem and come up with a mixed integer programming based algorithm. The simulation result shows that our method has good performances and is robust to errors in the data.
KW - Integer programming
KW - Path identification
KW - Sensor networks
KW - Social collective behavior
UR - https://www.scopus.com/pages/publications/84894131382
U2 - 10.1007/978-3-319-04048-6_6
DO - 10.1007/978-3-319-04048-6_6
M3 - Conference contribution
AN - SCOPUS:84894131382
SN - 9783319040479
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 56
EP - 67
BT - Behavior and Social Computing - Int. Workshop on Behavior and Social Informatics, BSI 2013 and Int. Workshop on Behavior and Social Informatics and Computing, BSIC 2013, Revised Selected Papers
PB - Springer Verlag
T2 - 2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013
Y2 - 3 August 2013 through 9 August 2013
ER -