Large-Scale Mobility Data

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Springer
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Analyzing large-scale human mobility data: a survey of ... - Springer
Implementing analysis methods on users’ location data enables various types of analysis on individuals’ mobility patterns. For example, user modeling can enable prediction of a user location, foreseeing the place in which the specific user will be situated in a particular time period of the day, based on historical … 展开
Place Modeling
Methods addressing place modeling can be divided into several categories, based on the way spatial environments are defined and organized. Traditional studies of … 展开
Trajectory Modeling
Analyzing trajectories is a key to understanding many of the questions related to transportation and human mobility. Trajectory is an abstraction of a route, … 展开
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Place Modeling
Trajectory Modeling
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Nature
https://www.nature.com › articles
Utilizing large-scale human mobility data to identify ... - Nature
2025年1月27日 · In this study, we analyze large-scale human mobility data from over 20 million individuals to investigate how visits to various locations, such as cafes and restaurants, …
标记:
Human Mobility Data
Geographic mobility
Mobility Data Study
Physical exercise
Large-Scale Mobility Data 的研究
arXiv.org
Predicting COVID-19 Spread from Large-Scale Mobility Data
To manage the COVID-19 epidemic effectively, decision-makers in public health need accurate forecasts of case numbers. A potential near real-time predictor of future case numbers is human mobility; however, research on the predictive power of mobility is lacking. To fill this gap, we introduce a nov...
作者: Amray Schwabe, …
已发布: 2021/06/01
页数: 9
arXiv.org
Mitigating biases in big mobility data: a case study of monitoring large-scale transit systems
Big mobility datasets (BMD) have shown many advantages in studying human mobility and evaluating the performance of transportation systems. However, the quality of BMD remains poorly understood. This study evaluates biases in BMD and develops mitigation methods. Using Google and Apple mobility data ...
作者: Feilong Wang, Xu…
已发布: 2024/07/16
页数: 25
ResearchGate
Analyzing large-scale human mobility data: a survey of machine learning methods and applications
Human mobility patterns reflect many aspects of life, from the global spread of infectious diseases to urban planning and daily commute patterns. In recent years, the prevalence of positioning methods and technologies, such as the global positioning system, cellular radio tower geo-positioning, and ...
已发布: 2019/03/01
DOI: 10.1007/s10115-0…
arXiv.org
Metropolitan Scale and Longitudinal Dataset of Anonymized Human Mobility Trajectories
Modeling and predicting human mobility trajectories in urban areas is an essential task for various applications. The recent availability of large-scale human movement data collected from mobile devices have enabled the development of complex human mobility prediction models. However, human mobility...
作者: Takahiro Yabe, K…
已发布: 2023/07/07
Cite As: arXiv:2307.03…
ScienceDirect
Unveiling large-scale commuting patterns based on mobile phone cellular network data
In this study, with Estonia as an example,we established an approach based on Hidden Markov Model to extract large-scale commuting patterns at different geographical levels using a massive amount of mobile phone cellular network data, which is referred to as Call detail record (CDR). The proposed mo...
已发布: 2020/12/01
Cited By: 0
Keywords: Commutin…
ScienceDirect
Resilience of Interdependent Urban Socio-Physical Systems using Large-Scale Mobility Data: Modeling Recovery Dynamics
Cities are complex systems comprised of socioeconomic systems relying on critical services delivered by multiple physical infrastructure networks. Due to interdependencies between social and physical systems, disruptions caused by natural hazards may cascade across systems, amplifying the impact of ...
已发布: 2021/12/01
Cited By: 0
Keywords: Resilience; …
FIB-LAB
http://fi.ee.tsinghua.edu.cn › public › publications
[PDF]
Passive Health Monitoring Using Large Scale Mobility Data
Specifically, there are three key challenges to conduct large scale health monitoring based on mobility data. First, collecting an appropriate mobility data source for health status...
标记:
Scale
Mobility
Nature
https://www.nature.com › articles
Distorted insights from human mobility data - Nature
2024年12月24日 · These results demonstrate the very large variability of mobility networks over different countries and data providers, pointing out differences that might bias models which …
标记:
Human Mobility Data
Geographic mobility
Large-Scale Mobility Data 的视频

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Predicting COVID-19 Spread from Large-Scale Mobility Data | Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
2021年8月13日
acm.org
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2:01
Mobility Perspectives: Telling the Mobility Story with Data
已浏览 5393 次2019年6月11日
YouTubeGraebel Relocation
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4:41
How to Measure Wheelchairs
已浏览 3万次2018年5月4日
YouTubeHome Care Medical/AeroCare
在 acm.org 上观看视频
MobileRec: A Large Scale Dataset for Mobile Apps Recommendation | Proceedings of the 46th International A…
2023年7月19日
acm.org
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2:21
Elderly Mobility Scale | EMS |
已浏览 555 次2023年11月3日
YouTubeBMH learning
arXiv.org
https://arxiv.org › abs
Predicting COVID-19 Spread from Large-Scale Mobility Data
2021年6月1日 · Specifically, we used mobility data from February through April 2020, amounting to approximately 1.5 billion trips. Trip counts were derived from large-scale telecommunication …
标记:
Covid Predictive Models
Covid-19 Spread Model
Publish Year:2021
Nature
https://www.nature.com › articles
Multiscale dynamic human mobility flow dataset in the U.S
2020年11月12日 · With the rapid development of information and communication technologies (ICT) and GPS embedded devices, large-scale mobile phone data provides an unprecedented …
标记:
Geographic mobility
Publish Year:2020
Dynamic verb
其他用户还问了以下问题
Is there a multiscale dynamic human mobility flow dataset?
Is there a multiscale dynamic human mobility flow dataset?
A notable study is by [ 40] who developed and open sourced a multiscale dynamic human mobility flow dataset using SafeGraph data. However, the dataset only covers the US limited by the single data source and is shared as individual downloadable files lacking interactive data accessibility.
ODT FLOW: Extracting, analyzing, and sharing multi-source multi ... - PL…
journals.plos.org
Why is large-scale mobile phone data important?
Why is large-scale mobile phone data important?
With the rapid development of information and communication technologies (ICT) and GPS embedded devices, large-scale mobile phone data provides an unprecedented opportunity in tracking human trajectories, which benefits research about human mobility patterns.
Multiscale dynamic human mobility flow dataset in the U.S. during t…
nature.com
Why do we need a scalable platform for human mobility data?
Why do we need a scalable platform for human mobility data?
In response to the soaring needs of human mobility data, especially during disaster events such as the COVID-19 pandemic, and to the 5 V challenges in big mobility data, we develop a scalable platform for extracting, querying, visualizing, and sharing multi-source multi-scale human mobility data.
ODT FLOW: Extracting, analyzing, and sharing multi-source multi ... - PL…
journals.plos.org
Why do we use mobility data?
Why do we use mobility data?
Mobility data were also found to represent human behavior in catastrophic events, e.g., the 2010 Haiti earthquake [9, 57] or the 2011 Japan earthquake . Models of mobility were used in designing public transportation systems , in taxicab allocation , and in performing crowd-sourcing tasks .
Analyzing large-scale human mobility data: a survey of ... - Springer
link.springer.com
arXiv.org
https://arxiv.org › abs
[2407.14541] Mitigating biases in big mobility data: a case study of ...
2024年7月16日 · It is shown that the mitigated BMD could generate valuable insights into large-scale public transit systems across 100+ US counties, revealing regional disparities of the …
标记:
Mobility Data Study
Navigational transit
Covid-19
ResearchGate
https://www.researchgate.net › publication
(PDF) Analyzing large-scale human mobility data: a …
2019年3月1日 · The efforts to mine significant patterns within large-scale, high-dimensional mobility data have solicited use of advanced analysis techniques, usually based on machine learning methods, and...
标记:
Human Mobility Data
Machine learning
Human Mobility Survey
plos.org
https://journals.plos.org › plosone › article
ODT FLOW: Extracting, analyzing, and sharing multi …
2021年8月5日 · Within the platform, an origin-destination-time (ODT) data model is proposed to work with scalable query engines to handle heterogenous mobility data in large volumes with extensive spatial coverage, which allows for …
标记:
Geographic mobility
PLOS ONE
arXiv.org
https://arxiv.org › abs
Metropolitan Scale and Longitudinal Dataset of Anonymized …
2023年7月7日 · To this end, we created an open-source, anonymized, metropolitan scale, and longitudinal (90 days) dataset of 100,000 individuals' human mobility trajectories, using mobile …
标记:
Human Mobility Data
arXiv:2307.03401 [cs.SI
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Analyzing large-scale human mobility data: a survey of ... - Springer

Utilizing large-scale human mobility data to identify ... - Nature

Passive Health Monitoring Using Large Scale Mobility Data

Distorted insights from human mobility data - Nature

Large-Scale Mobility Data 的视频

Predicting COVID-19 Spread from Large-Scale Mobility Data

Multiscale dynamic human mobility flow dataset in the U.S

ODT FLOW: Extracting, analyzing, and sharing multi-source multi ... - PL…

Multiscale dynamic human mobility flow dataset in the U.S. during t…

ODT FLOW: Extracting, analyzing, and sharing multi-source multi ... - PL…

Analyzing large-scale human mobility data: a survey of ... - Springer

[2407.14541] Mitigating biases in big mobility data: a case study of ...

(PDF) Analyzing large-scale human mobility data: a …

ODT FLOW: Extracting, analyzing, and sharing multi …

Metropolitan Scale and Longitudinal Dataset of Anonymized …

Large-Scale Mobility Data 的相关搜索

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