scholarly journals A Bimodal Model to Estimate Dynamic Metropolitan Population by Mobile Phone Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3431 ◽  
Author(s):  
Jie Feng ◽  
Yong Li ◽  
Fengli Xu ◽  
Depeng Jin
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Mobile Networks ◽  
Mobility Management ◽  
Population Distribution ◽  
Estimation Error ◽  
Population Estimation ◽  
Mobile Phone Data ◽  
Estimation Accuracy ◽  
Estimation Interval

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.

Research on the Traffic Simulation Platform Based on the Real-Time Mobile Phone Data

2012 ◽  
Vol 253-255 ◽  
pp. 1365-1368
Author(s):  
Ge Qi Qi ◽  
Jian Ping Wu ◽  
Yi Man Du
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Traffic Simulation ◽  
Rapid Development ◽  
Mobile Phone Data ◽  
Simulation Platform ◽  
Traffic Data ◽  
The Real ◽  
Real Time Traffic ◽  
Wide Range

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.

scholarly journals Evaluation for hypocenter estimation error in the southwestern Kuril trench using Japan and Russia joint seismic data

2020 ◽  
Author(s):  
Masayoshi Ichiyanagi ◽  
Mikhaylov Valentin ◽  
Dmitry Kostylev ◽  
Yuri Levin ◽  
Hiroaki Takahashi
Keyword(s):  
Real Time ◽  
Seismic Data ◽  
Estimation Error ◽  
Tsunami Warning ◽  
Disaster Mitigation ◽  
Border Zone ◽  
Japan Meteorological Agency ◽  
Estimation Accuracy ◽  
Waveform Data ◽  
Kuril Trench

Abstract The southwestern Kuril trench is seismically active due to the subduction of the Pacific plate. Great earthquakes in this zone have frequently induced fatal disasters. Seismic monitoring and hypocenter catalogues provide fundamental information on earthquake occurrence and disaster mitigation. Real-time hypocenter and magnitude estimates are extremely crucial data for tsunami warning systems. However, this region is located in the international border zone between Japan and Russia. The Japan Meteorological Agency and Russian Academy of Sciences have routinely determined hypocenters and issued earthquake information independently. Waveform data have not yet been exchanged internationally in real time. Here, we evaluated how a hypothetical Japan-Russia joint seismic network could potentially improve the hypocenter estimation accuracy. Experiments using numerical and observed data indicated that the joint network extended the distance over which hypocenters can be accurately determined over 100 km eastward compared to the Japan network only. This fact suggests that joint seismic data have the potential to improve the hypocenter accuracy in this region, which would provide improved performance in gathering disaster information at the moment of a tsunami warning.

scholarly journals Implementation of Mobile Phone Data Collection in the Conduct EPI Comprehensive Review in East and Southern African Countries

2021 ◽  
Vol Special Issue (2) ◽  
pp. 55-62
Author(s):  
Isah Mohammed Bello ◽  
Abubakar Sadiq Umar ◽  
Godwin Ubong Akpan ◽  
Joseph Okeibunor ◽  
Chukwudi Shibeshi ◽  
...  
Keyword(s):  
Data Collection ◽  
Mobile Phone ◽  
Real Time ◽  
Mobile Phones ◽  
Health Sector ◽  
Mobile Phone Data ◽  
Data Detection ◽  
Time Data ◽  
African Countries ◽  
Comprehensive Review

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.

Population distribution modelling at fine spatio-temporal scale based on mobile phone data

2020 ◽  
pp. 122-143
Author(s):  
Petr Kubíček ◽  
Milan Konečný ◽  
Zdeněk Stachoň ◽  
Jie Shen ◽  
Lukáš Herman ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Population Distribution ◽  
Temporal Scale ◽  
Mobile Phone Data ◽  
Distribution Modelling ◽  
Spatio Temporal

Real-Time Large-Scale Map Matching Using Mobile Phone Data

2017 ◽  
Vol 11 (4) ◽  
pp. 1-38 ◽  
Author(s):  
Essam Algizawy ◽  
Tetsuji Ogawa ◽  
Ahmed El-Mahdy
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Large Scale ◽  
Mobile Phone Data ◽  
Map Matching
Sign in / Sign up

Export Citation Format

Share Document