The use of mobile phone location data for traffic information

2004 ◽  
Author(s):  
J. White
Keyword(s):  
Mobile Phone ◽  
Traffic Information ◽  
Location Data

Travel mode recognition of urban residents using mobile phone data and MapAPI

2021 ◽  
pp. 239980832098300
Author(s):  
Zhenghong Peng ◽  
Guikai Bai ◽  
Hao Wu ◽  
Lingbo Liu ◽  
Yang Yu
Keyword(s):  
Urban Planning ◽  
Mobile Phone ◽  
Traffic Flow ◽  
Road Traffic ◽  
Urban Traffic ◽  
Phone Call ◽  
Traffic Information ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Travel Mode

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

scholarly journals Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Adrian M. Tompkins ◽  
Nicky McCreesh
Keyword(s):  
Mobile Phone ◽  
Malaria Transmission ◽  
Gravity Model ◽  
Mobile Phone Data ◽  
Agent Based ◽  
Migration Model ◽  
Location Data ◽  
Home Location ◽  
One Year ◽  
Overnight Stays

One year of mobile phone location data from Senegal is analysed to determine the characteristics of journeys that result in an overnight stay, and are thus relevant for malaria transmission. Defining the home location of each person as the place of most frequent calls, it is found that approximately 60% of people who spend nights away from home have regular destinations that are repeatedly visited, although only 10% have 3 or more regular destinations. The number of journeys involving overnight stays peaks at a distance of 50 km, although roughly half of such journeys exceed 100 km. Most visits only involve a stay of one or two nights away from home, with just 4% exceeding one week. A new agent-based migration model is introduced, based on a gravity model adapted to represent overnight journeys. Each agent makes journeys involving overnight stays to either regular or random locations, with journey and destination probabilities taken from the mobile phone dataset. Preliminary simulations show that the agentbased model can approximately reproduce the patterns of migration involving overnight stays.

scholarly journals Challenges in Contact Tracing by Mining Mobile Phone Location Data for COVID-19: Implications for Public Governance in South Africa

10.28945/4736 ◽  
2021 ◽  
Vol 16 ◽  
pp. 101-124
Author(s):  
Paul Kariuki ◽  
Lizzy O Ofusori ◽  
Prabhakar Rontala Subramanniam ◽  
Moses Okpeku ◽  
Maria L Goyayi
Keyword(s):  
Public Health ◽  
South Africa ◽  
Mobile Phone ◽  
Contact Tracing ◽  
Future Research ◽  
Public Governance ◽  
The Public ◽  
Location Data ◽  
Pertinent Data ◽  
Privacy And Confidentiality

Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving.

ESTIMATION OF THE NUMBER OF PEOPLE UNABLE TO GOING HOME AT DISASTER USING AGGREGATED MOBILE PHONE LOCATION DATA

2021 ◽  
Vol 76 (5) ◽  
pp. I_719-I_727
Author(s):  
Shinya YOSHIDA ◽  
Tomotaka USUI ◽  
Toshiyuki YAMAMOTO ◽  
Takayuki MORIKAWA
Keyword(s):  
Mobile Phone ◽  
Location Data

scholarly journals It Is All About Location: Smartphones and Tracking the Spread of COVID-19

2020 ◽  
Vol 6 (3) ◽  
pp. 205630512094825
Author(s):  
Jordan Frith ◽  
Michael Saker
Keyword(s):  
Mobile Phone ◽  
Contact Tracing ◽  
Mobile Phone Data ◽  
Locative Media ◽  
Location Data ◽  
Growing Body ◽  
Anonymized Data ◽  
Media Research ◽  
Data Visualizations

Mobile phone location data have become tied to understandings of and responses to the COVID-19 pandemic. Data visualizations have used mobile phone data to inform people about how mobility practices may be linked to the spread of the virus, and governments have explored contact tracing that relies upon mobile phone data. This article examines how these uses of location data implicate three particular issues that have been present in the growing body of locative media research: (1) anonymized data are often not anonymous, (2) location data are not always representative and can exacerbate inequality, and (3) location data are a key part of the extension of the surveillance state.

Interrogating ‘Digital Korea’: Mobile Phone Tracking and the Spatial Expansion of Labour Control

2011 ◽  
Vol 141 (1) ◽  
pp. 107-117 ◽  
Author(s):  
Kwang-Suk Lee
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Political System ◽  
Spatial Expansion ◽  
Mobile Phone Use ◽  
Business Interests ◽  
Location Data ◽  
Mobile Tracking ◽  
Private Corporations ◽  
Space Of Flows

This study investigates the realistic conditions of ‘digital Korea’, especially as they are exemplified by the Samsung SDI scandal in South Korea. Samsung SDI, the world's largest plasma TV maker and a subsidiary of the Samsung Group, has fallen under suspicion due to using illegally cloned mobile phones to track the location data of some activist workers who tried to organise a union. The study stresses that this example of mobile tracking represents the shady side of mobile phone use created by management's excessive desire for labour control, and confirms that mobile tracking techniques make possible the spatial expansion of the scope of power. The spatial vocabulary of power is not totalitarian, but dispersed and nomadic in action, and resides in the space of ‘flows’ constructed by electronic impulses. This study discloses that, for private corporations, mobile tracking facilitates a form of efficient, invisible labour control over ‘targeted’ workers, even outside the workplace. It concludes that the control of labourers in Korea has been reinforced by the confluence of business interests, the under-developed political system and a societal lack of interest in privacy.

scholarly journals Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data

2018 ◽  
Vol 108 ◽  
pp. 64-67 ◽  
Author(s):  
Susan Athey ◽  
David Blei ◽  
Robert Donnelly ◽  
Francisco Ruiz ◽  
Tobias Schmidt
Keyword(s):  
Mobile Phone ◽  
Travel Time ◽  
Consumer Preferences ◽  
Mobile Location ◽  
Location Data ◽  
Consumer Choices ◽  
Using Data

We estimate a model of consumer choices over restaurants using data from several thousand anonymous mobile phone users. Restaurants have latent characteristics (whose distribution may depend on restaurant observables) that affect consumers' mean utility as well as willingness to travel to the restaurant, while each user has distinct preferences for these latent characteristics. We analyze how consumers reallocate their demand after a restaurant closes to nearby restaurants versus more distant restaurants, comparing our predictions to actual outcomes. We also address counterfactual questions such as what type of restaurant would attract the most consumers in a given location.

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