A Geo-Social Data Model for Moving Objects

Author(s):  
Hengcai Zhang ◽  
Feng Lu ◽  
Jie Chen
2019 ◽  
Vol 153 ◽  
pp. 74-95 ◽  
Author(s):  
Mingxiang Feng ◽  
Shih-Lung Shaw ◽  
Zhixiang Fang ◽  
Hao Cheng

2012 ◽  
Vol 17 (1) ◽  
pp. 125-172 ◽  
Author(s):  
Jianqiu Xu ◽  
Ralf Hartmut Güting

Author(s):  
Haoshu Cai ◽  
Yu Guo ◽  
Kun Lu

In the data-rich manufacturing environment, the production process of work-in-process is described and presented by trajectories with manufacturing significance. However, advanced approaches for work-in-process trajectory data analytics and prediction are comparatively inadequate. However, the location prediction of moving objects has drawn great attention in the manufacturing field. Yet most approaches for predicting future locations of objects are originally applied in geography domain. When applied to manufacturing shop floor, the prediction results lack manufacturing significance. This article focuses on predicting the next locations of work-in-process in the workshop. First, a data model is introduced to map the geographic trajectories into the logical space, in order to convert the manufacturing information into logical features. Based on the data model, a prediction method is proposed to predict the next locations using frequent trajectory patterns. A series of experiments are performed to examine the prediction method. The experiment results illustrate the impacts of the user-defined factors and prove that the proposed method is effective and efficient.


2010 ◽  
Vol 7 (4) ◽  
pp. 931-945 ◽  
Author(s):  
Ivana Nizetic ◽  
Kresimir Fertalj

Whereas research on moving objects is involved in a variety of different application areas, models and methods for movement prediction are often tailored to the specific type of moving objects. However, in most cases, prediction models are taking only historical location in consideration, while characteristics specific to certain type of moving objects are ignored. In this paper, we presented a conceptual model for movement prediction independent on an application area and data model of moving objects considering various object?s characteristics. Related work is critically evaluated, addressing advantages, possible problems and places for improvement. Generic model is proposed, based on an idea to encompass missing pieces in related work and to make the model as general as possible. Prediction process is illustrated on three case studies: prediction of the future location of vehicles, people and wild animals, in order to show their differences and to show how the process can be applied to all of them.


2013 ◽  
Vol 18 (1) ◽  
pp. 66-88 ◽  
Author(s):  
Vania Bogorny ◽  
Chiara Renso ◽  
Artur Ribeiro de Aquino ◽  
Fernando de Lucca Siqueira ◽  
Luis Otavio Alvares

2000 ◽  
Vol 29 (2) ◽  
pp. 319-330 ◽  
Author(s):  
Luca Forlizzi ◽  
Ralf Hartmut Güting ◽  
Enrico Nardelli ◽  
Markus Schneider

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