scholarly journals Passive Wi-Fi monitoring in the wild: a long-term study across multiple location typologies

2020 ◽  
Author(s):  
Miguel Ribeiro ◽  
Nuno Nunes ◽  
Valentina Nisi ◽  
Johannes Schöning
Keyword(s):  
Public Transportation ◽  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Tracking System ◽  
Human Mobility ◽  
Transportation Systems ◽  
Mobility Patterns ◽  
Systematic Analysis ◽  
Long Term Study

Abstract In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area of 2.8 km2. In this paper we provide a systematic analysis of the data and discuss how our low-cost approach can be used to help communities and policymakers to make decisions to improve people’s mobility at high temporal and spatial resolution by inferring presence characteristics against several sources of ground truth. Also, we present an automatic classification technique that can identify location types based on collected data.

scholarly journals Modelling human mobility patterns using photographic data shared online

2015 ◽  
Vol 2 (8) ◽  
pp. 150046 ◽  
Author(s):  
Daniele Barchiesi ◽  
Tobias Preis ◽  
Steven Bishop ◽  
Helen Susannah Moat
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Learning Algorithm ◽  
Human Mobility ◽  
Transportation Systems ◽  
Mobility Patterns ◽  
Online Data ◽  
Photo Sharing ◽  
Wide Range ◽  
The Uk

Humans are inherently mobile creatures. The way we move around our environment has consequences for a wide range of problems, including the design of efficient transportation systems and the planning of urban areas. Here, we gather data about the position in space and time of about 16 000 individuals who uploaded geo-tagged images from locations within the UK to the Flickr photo-sharing website. Inspired by the theory of Lévy flights, which has previously been used to describe the statistical properties of human mobility, we design a machine learning algorithm to infer the probability of finding people in geographical locations and the probability of movement between pairs of locations. Our findings are in general agreement with official figures in the UK and on travel flows between pairs of major cities, suggesting that online data sources may be used to quantify and model large-scale human mobility patterns.

scholarly journals Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models

2017 ◽  
Vol 4 (5) ◽  
pp. 160950 ◽  
Author(s):  
Cecilia Panigutti ◽  
Michele Tizzoni ◽  
Paolo Bajardi ◽  
Zbigniew Smoreda ◽  
Vittoria Colizza
Keyword(s):  
Infectious Disease ◽  
Mobile Phone ◽  
Urban Areas ◽  
Large Scale ◽  
Human Mobility ◽  
Mobile Phone Data ◽  
Disease Models ◽  
Mobility Patterns ◽  
Mobility Data ◽  
Infectious Disease Models

The recent availability of large-scale call detail record data has substantially improved our ability of quantifying human travel patterns with broad applications in epidemiology. Notwithstanding a number of successful case studies, previous works have shown that using different mobility data sources, such as mobile phone data or census surveys, to parametrize infectious disease models can generate divergent outcomes. Thus, it remains unclear to what extent epidemic modelling results may vary when using different proxies for human movements. Here, we systematically compare 658 000 simulated outbreaks generated with a spatially structured epidemic model based on two different human mobility networks: a commuting network of France extracted from mobile phone data and another extracted from a census survey. We compare epidemic patterns originating from all the 329 possible outbreak seed locations and identify the structural network properties of the seeding nodes that best predict spatial and temporal epidemic patterns to be alike. We find that similarity of simulated epidemics is significantly correlated to connectivity, traffic and population size of the seeding nodes, suggesting that the adequacy of mobile phone data for infectious disease models becomes higher when epidemics spread between highly connected and heavily populated locations, such as large urban areas.

Discovery of Public Transportation Patterns Through the Use of Big Data Technologies for Urban Mobility

2019 ◽  
Author(s):  
Hugo Antunes ◽  
Paulo Figueiras ◽  
Ruben Costa ◽  
Joel Teixeira ◽  
Ricardo Jardim-Gonçalves
Keyword(s):  
Big Data ◽  
Public Transport ◽  
Public Transportation ◽  
Urban Areas ◽  
Human Mobility ◽  
Transportation Network ◽  
Transport Network ◽  
Special Focus ◽  
Mobility Patterns ◽  
Big Data Technologies

Abstract Big cities show a wide public transport network that allows people to travel within the cities. However, with the overcrowding of big urban areas, the demand for new mobility strategies has increasing. Every day, citizens need to commute fast, easily and comfortable, which is not always easy due to the complexity of the public transport network. Therefore, this paper aims to explore the ability of Big Data technologies to cope with data collected from public transportation, by inferring automatically and continuously, complex mobility patterns about human mobility, in the form of insightful indicators (such as connections, transshipments or pendular movements), creating a new perspective in public transports data analytics. With special focus on the Lisbon public transport network, the challenge addressed by this work, is to analyze the demand and supply side of transportation network of Lisbon metropolitan area, considering ticketing data provided by the different transportation operators, which until now were essentially obtained through observation methods and surveys.

scholarly journals Impact of Culture on Rural Built Environment

2019 ◽  
Vol 8 (10S) ◽  
pp. 78-84
Keyword(s):  
Built Environment ◽  
Natural Resources ◽  
Rural Areas ◽  
Human Activities ◽  
Urban Areas ◽  
Large Scale ◽  
Future Generation ◽  
Transportation Systems ◽  
Rural Regions ◽  
The Common

The term “built environment” refers to the human made or modified physical surroundings in which people live, work and play. These places and spaces include our homes, communities, schools, workplaces, parks/recreations areas, business areas and transportation systems, and vary in size from large-scale urban areas to smaller rural developments. Based on human activities, the environment was created to obtain the basic needs of people. The regular human activities for many generations to prepare their needs are considered as culture. Hence based on culture, the environment was built and maintained for future generation. Regions are separated into two types based on production occurs in rural area and trading developed in urban. In olden days, most of the places are rural because of the undevelopment in transport system. The activities involved in preparing food, shelter and other needs are the common factors to build rural environment. Natural resources are the basic factor that decides the build environment and culture of human in rural regions. By analyzing the natural resources, the cultural impacts are determined based on building environment in rural areas

scholarly journals Clustered embedding using deep learning to analyze urban mobility based on complex transportation data

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249318
Author(s):  
Sung-Bae Cho ◽  
Jin-Young Kim
Keyword(s):  
Deep Learning ◽  
Public Transportation ◽  
Urban Areas ◽  
Large Scale ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Large Scale Data ◽  
Physical Shape ◽  
Novel Method ◽  
Personalized Mobility

Urban mobility is a vital aspect of any city and often influences its physical shape as well as its level of economic and social development. A thorough analysis of mobility patterns in urban areas can provide various benefits, such as the prediction of traffic flow and public transportation usage. In particular, based on its exceptional ability to extract patterns from complex large-scale data, embedding based on deep learning is a promising method for analyzing the mobility patterns of urban residents. However, as urban mobility becomes increasingly complex, it becomes difficult to embed patterns into a single vector because of its limited capacity. In this paper, we propose a novel method for analyzing urban mobility based on deep learning. The proposed method involves clustering mobility patterns and embedding them to capture their implicit meaning. Clustering groups mobility patterns based on their spatiotemporal characteristics, and embedding provides meaningful information regarding both individual residents (i.e., personalized mobility) and all residents as a whole, enabling a more effective analysis of mobility patterns. Experiments were performed to predict the successive points of interest (POIs) based on transportation data collected from 1.5 million citizens in a large metropolitan city; the results demonstrate that the proposed method achieves top-1, 3, and 5 accuracies of 73.64%, 88.65%, and 91.54%, respectively, which are much higher than those of the conventional method (59.48%, 75.85%, and 80.1%, respectively). We also demonstrate that the proposed method facilitates the analysis of urban mobility through arithmetic operations between POI vectors.

scholarly journals Urbanized rural areas: Identification, spatiotemporal patterns, socioeconomic characteristics, and impacts on sustainable development

2021 ◽  
Author(s):  
Zhichao He ◽  
Marcin Spyra ◽  
Qinghai Guo
Keyword(s):  
Sustainable Development ◽  
Spatial Data ◽  
Public Transportation ◽  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Rural Poverty ◽  
Biodiversity Loss ◽  
Urban Centers ◽  
Socioeconomic Characteristics

Abstract Sustainable development studies tend to give urban areas a priority seat, with rural areas cast in an inferior role. Despite of the growing urbanization, rural areas still are homes of billions of people universally suffering from poverty, hunger, disease, poor education. The urbanized rural areas, where population, economy, and built-up land area are higher than urban areas, present the opportunities and challenges to sustainable development. Using large-scale and high-granular spatial data (e.g., population, economy, land-use) from Fujian Province of China, we identified 69, 123, and 213 urbanized rural areas in 1995, 2005, and 2015 from 14,136 village-level administrative units. Spatial agglomeration, proximity to well-developed urban centers, and transportation accessibility are the important spatial factors influencing the development of the urbanized rural areas. Furthermore, we investigated the socioeconomic characteristics of the urbanized rural areas based on the Point of Interest data and found the urbanized rural areas had urban-like housing model, diverse non-agricultural livelihoods, complex road networks, mature public transportation, and better access to medical service. Our results suggest that the urbanized rural areas contribute to sustainable development in terms of economy and society, such as alleviating rural poverty, reducing urban-rural inequality, improving health. However, the environment impacts of the urbanized rural areas should be emphasized because urban-like socioeconomic activities and land conversions toward built-up land may lead to increased energy consumption, land degradation and biodiversity loss in rural areas.

The Economic Imperative: Cities Need Migrants

2021 ◽  
pp. 001946622110132
Author(s):  
Astha Agarwalla ◽  
Errol D’Souza
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Market Failure ◽  
Jel Classification ◽  
Industry Concentration ◽  
Wage Curve ◽  
Economic Agents ◽  
Reverse Migration ◽  
Local Labour

The policy responses to Covid-19 have triggered large-scale reverse migration from cities to rural areas in developing countries, exposing the vulnerability of migrants living precarious lives in cities, giving rise to debates asserting to migration as undesirable and favouring policy options to discourage the process. However, the very basis of spatial concentration and formation of cities is presence of agglomeration economies, benefits accruing to economic agents operating in cities. Presence of these agglomeration benefits in local labour markets manifests themselves in the form of an upward sloping wage curve in urban areas. We estimate the upward sloping wage curve for various size classes of cities in Indian economy and establish the presence of positive returns to occupation and industry concentration at urban locations. Controlling for worker-specific characteristics influencing wages, we establish that higher the share of an industry or an occupation in local employment as compared to national economy, the desirability of firms to pay higher wages increases. For casual labourers, occupational concentration results in higher wages. However, impact of industry concentration varies across sectors. Results supporting presence of upward sloping urban wage curve, therefore, endorse policies to correct the market failure in cities and promote migration as a desirable process. JEL Classification Codes: J2, R2

scholarly journals GNSS RUMS: GNSS Realistic Urban Multiagent Simulator for Collaborative Positioning Research

2021 ◽  
Vol 13 (4) ◽  
pp. 544
Author(s):  
Guohao Zhang ◽  
Bing Xu ◽  
Hoi-Fung Ng ◽  
Li-Ta Hsu
Keyword(s):  
Urban Area ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Large Scale ◽  
Transportation Systems ◽  
Accurate Localization ◽  
Gnss Receivers ◽  
Multipath Signal ◽  
Scale Test ◽  
Error Behavior

Accurate localization of road agents (GNSS receivers) is the basis of intelligent transportation systems, which is still difficult to achieve for GNSS positioning in urban areas due to the signal interferences from buildings. Various collaborative positioning techniques were recently developed to improve the positioning performance by the aid from neighboring agents. However, it is still challenging to study their performances comprehensively. The GNSS measurement error behavior is complicated in urban areas and unable to be represented by naive models. On the other hand, real experiments requiring numbers of devices are difficult to conduct, especially for a large-scale test. Therefore, a GNSS realistic urban measurement simulator is developed to provide measurements for collaborative positioning studies. The proposed simulator employs a ray-tracing technique searching for all possible interferences in the urban area. Then, it categorizes them into direct, reflected, diffracted, and multipath signal to simulate the pseudorange, C/N0, and Doppler shift measurements correspondingly. The performance of the proposed simulator is validated through real experimental comparisons with different scenarios based on commercial-grade receivers. The proposed simulator is also applied with different positioning algorithms, which verifies it is sophisticated enough for the collaborative positioning studies in the urban area.

scholarly journals Is global dimming and brightening in Japan limited to urban areas?

2016 ◽  
Author(s):  
Katsumasa Tanaka ◽  
Atsumu Ohmura ◽  
Doris Folini ◽  
Martin Wild ◽  
Nozomu Ohkawara
Keyword(s):  
Solar Radiation ◽  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Temporal Trends ◽  
Surface Radiation ◽  
Surface Solar Radiation ◽  
Decadal Time Scale ◽  
Global Dimming ◽  
Urban And Rural Areas

Abstract. Observations worldwide indicate secular trends of all-sky surface solar radiation on decadal time scale, termed global dimming and brightening. Accordingly, the observed surface radiation in Japan generally shows a strong decline till the end of the 1980s and then a recovery toward around 2000. Because a substantial number of measurement stations are located within or proximate to populated areas, one may speculate that the observed trends are strongly influenced by local air pollution and are thus not of large-scale significance. This hypothesis poses a serious question as to what regional extent the global dimming and brightening are significant: Are the global dimming and brightening truly global phenomena, or regional or even only local? Our study focused on 14 meteorological observatories that measured all-sky surface solar radiation, zenith transmittance, and maximum transmittance. On the basis of municipality population time series, historical land use maps, recent satellite images, and actual site visits, we concluded that eight stations had been significantly influenced by urbanization, with the remaining six stations being left pristine. Between the urban and rural areas, no marked differences were identified in the temporal trends of the aforementioned meteorological parameters. Our finding suggests that global dimming and brightening in Japan occurred on a large scale, independently of urbanization.

scholarly journals Flying Car Transportation System: Advances, Techniques, and Challenges

2020 ◽  
Author(s):  
Gaofeng pan ◽  
Mohamed-Slim Alouini
Keyword(s):  
Public Transportation ◽  
Traffic Congestion ◽  
Large Scale ◽  
Ethical Issues ◽  
Transportation Systems ◽  
Long Distance ◽  
Environmental Friendliness ◽  
Safety Issues ◽  
Inherent Nature ◽  
Car Transportation

In order to fulfill transportation demands, people have well-explored ground, waterborne, and high-altitude spaces (HAS) for transportation purposes, as well as the underground space under cities (namely, subway systems). However, due to the increased burdens of population and urbanization in recent decades, huge pressures on public transportation and freight traffic are introduced to cities, plaguing the governors and constraining the development of economics. By observing the fact that near-ground space (NGS) has rarely been utilized, researchers and practitioners started to re-examine, propose and develop flying cars, which are not a totally novel idea, aiming at solving the traffic congestion problem and releasing the strains of cities. Flying cars completely differ from traditional grounded transportation systems, where automobiles/trains are suffering track limitations and are also different from the air flights in HAS for long-distance transfer. Therefore, while observing the lack of specific literature on flying cars and flying car transportation systems (FCTS), this paper is motivated to study the advances, techniques, and challenges of FCTS imposed by the inherent nature of NGS transportation and to devise useful proposals for facilitating the construction and commercialization of FCTS, as well as to facilitate the readers understanding of the incoming FCTS. We first introduce the increased requirements for transportation and address the advantages of flying cars. Next, a brief overview of the developing history of flying cars is presented in view of both timeline and technique categories. Then, we discuss and compare the state of the art in the design of flying cars, including take-off \& landing (TOL) modes, pilot modes, operation modes, and power types, which are respectively related to the adaptability, flexibility & comfort, stability & complexity, environmental friendliness of flying cars. Additionally, since large-scale operations of flying cars can improve the aforementioned transportation problem, we also introduce the designs of FCTS, including path and trajectory planning, supporting facilities and commercial designs. Finally, we discuss the challenges which might be faced while developing and commercializing FCTS from three aspects: safety issues, commercial issues, and ethical issues.

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