Real-time people movement estimation in large disasters from several kinds of mobile phone data

Author(s):  
Yoshihide Sekimoto ◽  
Akihito Sudo ◽  
Takehiro Kashiyama ◽  
Toshikazu Seto ◽  
Hideki Hayashi ◽  
...  
2012 ◽  
Vol 253-255 ◽  
pp. 1365-1368
Author(s):  
Ge Qi Qi ◽  
Jian Ping Wu ◽  
Yi Man Du

With the rapid development of the society, the transportation system has become more complicated and vulnerable. For simulating the real-time traffic condition of the whole city, a wide range of OD matrix data are needed which are hard to collect in whole based on the present conventional methods. The paper raises a feasible design of the traffic simulation platform based on the real-time mobile phone data. The popularity and development of mobile phones make the vast amounts of real-time traffic data can be collected and usable. With the help of the GIS module, dynamic OD traffic generation module and other related modules, the real-time mobile phone data will be converted to the valuable traffic data and applied to the traffic simulation platform.


2021 ◽  
Vol Special Issue (2) ◽  
pp. 55-62
Author(s):  
Isah Mohammed Bello ◽  
Abubakar Sadiq Umar ◽  
Godwin Ubong Akpan ◽  
Joseph Okeibunor ◽  
Chukwudi Shibeshi ◽  
...  

Mobile phone data collection tools are increasingly becoming very usable collecting, collating and analysing data in the health sector. In this paper, we documented the experiences with mobile phone data collection, collation and analysis in 5 countries of the East and Southern African, using Open Data Kit (ODK), where questionnaires were designed and coded on an XML form, uploaded and data collected using Android-Based mobile phones, with a web-based system to monitor data in real-time during EPI comprehensive review. The ODK interface supports in real-time monitoring of the flow of data, detection of missing or incomplete data, coordinate location of all locations visited, embedded charts for basic analysis. It also minimized data quality errors at entry level with the use of validation codes and constraint developed into the checklist. These benefits, combined with the improvement that mobile phones offer over paper-based in terms of timeliness, data loss, collation, and real-time data collection, analysis and uploading difficulties, make mobile phone data collection a feasible method of data collection that needs to be further explored in the conduct of all surveys in the organization.


2017 ◽  
Vol 11 (4) ◽  
pp. 1-38 ◽  
Author(s):  
Essam Algizawy ◽  
Tetsuji Ogawa ◽  
Ahmed El-Mahdy

2015 ◽  
Vol 16 (5) ◽  
pp. 2551-2572 ◽  
Author(s):  
Andreas Janecek ◽  
Danilo Valerio ◽  
Karin Anna Hummel ◽  
Fabio Ricciato ◽  
Helmut Hlavacs

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3431 ◽  
Author(s):  
Jie Feng ◽  
Yong Li ◽  
Fengli Xu ◽  
Depeng Jin

Accurate, real-time and fine-spatial population distribution is crucial for urban planning, government management, and advertisement promotion. Limited by technics and tools, we rely on the census to obtain this information in the past, which is coarse and costly. The popularity of mobile phones gives us a new opportunity to investigate population estimation. However, real-time and accurate population estimation is still a challenging problem because of the coarse localization and complicated user behaviors. With the help of the passively collected human mobility and locations from the mobile networks including call detail records and mobility management signals, we develop a bimodal model beyond the prior work to better estimate real-time population distribution at metropolitan scales. We discuss how the estimation interval, space granularity, and data type will influence the estimation accuracy, and find the data collected from the mobility management signals with the 30 min estimation interval performs better which reduces the population estimation error by 30% in terms of Root Mean Square Error (RMSE). These results show us the great potential of using bimodal model and mobile phone data to estimate real-time population distribution.


2019 ◽  
Vol 7 (1) ◽  
pp. 77-84
Author(s):  
Jin Ki Eom ◽  
Kwang-Sub Lee ◽  
Ho-Chan Kwak ◽  
Ji Young Song ◽  
Myeong-Eon Seong

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