Abstract
Calculating the influence of facilities is an important part of urban computing, which adopts sensing technology to obtain people’s movement patterns in urban spaces and then applies this information to discover many hidden issues our cities face today. Influence of facilities is affected by people’s daily activities such as work and relax. In this paper, we compute the influence of facilities in real time and predict their future influence under a grid partition method. We Next predict influence changes of facilities over dynamic objects using trajectory based markov model. We conduct evaluation using a real world dataset, including one-month taxi trajectories with 27,000 taxis and 1000 facilities. Experimental results shows that our solution requires computation time close to 0.1 seconds and achieves an accuracy of 85 %.
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Acknowledgment
This work was supported in part by the National Natural Science Foundation of China (Grant No. 61202066, 61472418), and the "Strategic Priority Research Program" of the Chinese Academy of Sciences (Grant No. XDA06040101).
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Wang, H., Li, Q., Yi, F., Han, Q., Sun, L. (2015). Influential Spatial Facility Prediction over Dynamic Objects. In: Xu, K., Zhu, H. (eds) Wireless Algorithms, Systems, and Applications. WASA 2015. Lecture Notes in Computer Science(), vol 9204. Springer, Cham. https://doi.org/10.1007/978-3-319-21837-3_52
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DOI: https://doi.org/10.1007/978-3-319-21837-3_52
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