The Experts below are selected from a list of 2157 Experts worldwide ranked by ideXlab platform
I Hanski - One of the best experts on this subject based on the ideXlab platform.
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A New GPS–GS GSM-Based M-Method to Study Behavior of Brown Bears
Wildlife Society Bulletin, 2006Co-Authors: Janne Sundell, Ilpo Kojola, I HanskiAbstract:We report a new me method thod of studying brow brown bear ear (Ursus arctos arctos) behavior. ehavior. The meth method combines ombines the he technologies of Global Posit Positioning oning Systems (GPS) and Global lobal Syste ystem for or Mobi Mobile le Communicat Communication ion (GSM). A GPS–GSM collar on a bear ear locates ocates itself with the help of a GPS modul module, while the GSM module sends the locatio ocation informat nformation on to the researcher as SMS (short) me message ssage via a GSM mobil Mobile Phone Network. etwork. The collar ollar is interactive and can an receive SMS commands commands, for instance, nstance, to adjust djust the interva nterval at which location information nformation is transmitted. We tested the he method in experiments in which people equipp equipped ed with GPS–GSM Mobile Phones approached a GPS–GSM- collared bear. Spatial locations ocations of the bear ear and the he approaching person ersons are displa displayed yed on th the digital igital map on the he computer scre screen en in real-time. The dispers ispersion on of spatial information was as 2.5 m, and th the success uccess rate in the experiments was 81.2 1.2% (new spatial locations successfully received when requested). The method proved to be useful and accurate enough to study the he behavior of bears ears (e.g., escape initiation distance) istance) in the proximity of humans. We believe the methodology presen resented ted will hel help rese researchers archers to better understan understand bear ear behavior and develop strateg strategies ies to minimize inimize negative bear– human interactions. nteractions. Rapid apid data transmission creates new opportunities for anim animal al trackin tracking in gener eneral. al. We believe that the GPS mobil Mobile Phone- Phonebased based tracking will ill become the most cost-effective ost-me method thod for studying large animals nimals in areas servic serviced ed by Mobile Phone Networks. Key wo words rds behavior, brown bear, Global Positioning Systems, Global System for Mobile Communications, human contact, Ursus arctos.
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A New GPS-GSM-Based Method to Study Behavior of Brown Bears
Wildlife Society Bulletin, 2006Co-Authors: Janne Sundell, Ilpo Kojola, I HanskiAbstract:We report a new method of studying brown bear (Ursus arctos) behavior. The method combines the technologies of Global Positioning Systems (GPS) and Global System for Mobile Communication (GSM). A GPS–GSM collar on a bear locates itself with the help of a GPS module, while the GSM module sends the location information to the researcher as SMS (short) message via a GSM Mobile Phone Network. The collar is interactive and can receive SMS commands, for instance, to adjust the interval at which location information is transmitted. We tested the method in experiments in which people equipped with GPS–GSM Mobile Phones approached a GPS–GSM-collared bear. Spatial locations of the bear and the approaching persons are displayed on the digital map on the computer screen in real-time. The dispersion of spatial information was 2.5 m, and the success rate in the experiments was 81.2% (new spatial locations successfully received when requested). The method proved to be useful and accurate enough to study the behavior of bears (e.g., escape initiation distance) in the proximity of humans. We believe the methodology presented will help researchers to better understand bear behavior and develop strategies to minimize negative bear– human interactions. Rapid data transmission creates new opportunities for animal tracking in general. We believe that the GPS Mobile Phonebased tracking will become the most cost-effective method for studying large animals in areas serviced by Mobile Phone Networks.
Carlo Ratti - One of the best experts on this subject based on the ideXlab platform.
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inferring and modeling migration flows using Mobile Phone Network data
IEEE Access, 2019Co-Authors: Soranan Hankaew, Santi Phithakkitnukoon, Merkebe Getachew Demissie, Lina Kattan, Zbigniew Smoreda, Carlo RattiAbstract:Estimating migration flows and forecasting future trends is important, both to understand the causes and effects of migration and to implement policies directed at supplying particular services. Over the years, less research has been done on modeling migration flows than the efforts allocated to modeling other flow types, for instance, commute. Limited data availability has been one of the major impediments for empirical analyses and for theoretical advances in the modeling of migration flows. As a migration trip takes place much less frequent compared to the commute, it requires a longitudinal set of data for the analysis. This study makes use a massive Mobile Phone Network data to infer migration trips and their distribution. Insightful characteristics of the inferred migration trips are revealed, such as intra/inter-district migration flows, migration distance distribution, and origin-destination (O-D) movements. For migration trip distribution modelling, log-linear model, traditional gravity model, and recently introduced radiation model were examined with different approaches taken in defining parameters for each model. As the result, the gravity and log-linear models with a direct distance (displacement) used as its travel cost and district centroids used as the reference points perform best among the other alternative models. A radiation model that considers district population performs best among the radiation models, but worse than that of the gravity and log-linear models.
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Uncovering the Directional Heterogeneity of an Aggregated Mobile Phone Network
Transactions in Gis, 2014Co-Authors: Stanislav Sobolevsky, Carlo Ratti, Alexander Amini, Chenghu ZhouAbstract:The aggregated Mobile Phone Network (AMPN) (i.e. the calling time or numbers are aggregated at every vertex), which records the call volume between different places over time, has been studied extensively to reveal the mobility patterns of residents, etc. Nevertheless, most previous works were implemented based on the non-directionality of the Network model. This simplification may overlook some important characteristics of AMPN. To explore the AMPN as a directional Network model, we introduce the concept of directional heterogeneity in the study of AMPN data. The heterogeneity is twofold: (1) the imbalance of vertex (difference between outgoing and incoming calls of the vertex); and (2) the reciprocity of each edge (difference between the directed weights of the same edge). Taking the data of Singapore as an example, we systematically analyze the directional heterogeneity of AMPN. Our findings include three aspects. First, the AMPN shows as more unbalanced in the night-time than in the daytime, and its imbalance decreases as vertex granularity increases. Second, the directional heterogeneity varied with locations. Specifically, the residential area is dominated by deficits and others by surpluses. Third, the trajectories of incoming and outgoing calls follow a similar geographical pattern (i.e. southeast-north-south-north-southeast), indicating the calling behavior and routine mobility of users over time and space.
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Eigenplaces: analysing cities using the space-time structure of the Mobile Phone Network
ENVIRON PLANN B, 2009Co-Authors: Carlo RattiAbstract:Several attempts have already been made to use telecommunications Networks for urban research, but the datasets employed have typically been neither dynamic nor fine grained. Against this research backdrop the Mobile Phone Network offers a compelling compromise between these extremes: it is both highly Mobile and yet still localisable in space. Moreover, the Mobile Phone's enormous and enthusiastic adoption across most socioeconomic strata makes it a uniquely useful toot for conducting large-scale, representative behavioural research. In this paper we attempt to connect telecoms usage data from Telecom Italia Mobile (TIM) to a geography of human activity derived from data on commercial premises advertised through Pagine Gialle, the Italian 'Yellow Pages'. We then employ eigendecomposition-a process similar to factoring but suitable for this complex dataset-to identify and extract recurring patterns of Mobile Phone usage. The resulting eigenplaces support the computational and comparative analysis of space through the tens of telecommuniations usage and enhance our understanding of the city as a 'space of flows'.
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Scaling behaviors in the communication Network between cities
Proceedings - 12th IEEE International Conference on Computational Science and Engineering CSE 2009, 2009Co-Authors: Gautier Krings, Francesco Calabrese, Carlo Ratti, Vincent D BlondelAbstract:Researchers have been unable to predict the large-scale features of aggregate social Networks. We analyze the anonymous communications patterns of 2.5 million customers of a Belgian Mobile Phone operator. With these communications, we construct the social Network of the customers, that we call microscopic Network. Grouping customers together by billing address city, we obtain a social Network of cities, which we call the macroscopic Network, is built from 571 towns and cities in Belgium. Using the Mobile Phone Network, we are able to show that the macroscopic Network has both a degree distribution and edge weight distribution with lognormal characteristics. We find that inter-city communications can be characterized by a gravity model: the intensity of communication between two cities is proportional to the product of the two populations divided by the square of the distance between them. Furthermore, we observe that intra-urban communications scale superlinearly with city population.
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Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network:
Environment and Planning B-planning & Design, 2009Co-Authors: Jonathan Reades, Francesco Calabrese, Carlo RattiAbstract:Several attempts have already been made to use telecommunications Networks for urban research, but the datasets employed have typically been neither dynamic nor fine grained. Against this research backdrop the Mobile Phone Network offers a compelling compromise between these extremes: it is both highly Mobile and yet still localisable in space. Moreover, the Mobile Phone’s enormous and enthusiastic adoption across most socioeconomic strata makes it a uniquely useful tool for conducting large-scale, representative behavioural research. In this paper we attempt to connect telecoms usage data from Telecom Italia Mobile (TIM) to a geography of human activity derived from data on commercial premises advertised through Pagine Gialle, the Italian ‘Yellow Pages’. We then employ eigendecomposition—a process similar to factoring but suitable for this complex dataset—to identify and extract recurring patterns of Mobile Phone usage. The resulting eigenplaces support the computational and comparative analysis of space through the lens of telecommuniations usage and enhance our understanding of the city as a ‘space of flows’.
Francesco Calabrese - One of the best experts on this subject based on the ideXlab platform.
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data driven transit Network design from Mobile Phone trajectories
IEEE Transactions on Intelligent Transportation Systems, 2016Co-Authors: Fabio Pinelli, Francesco Calabrese, Rahul Nair, Michele Berlingerio, Giusy Di Lorenzo, Marco Luca SbodioAbstract:This paper presents a data-driven method for transit Network design that relies on a large sample of user location data available from Mobile Phone telecommunication Networks. Such data provide opportunistic sensing and the means for transit operators to match supply with mobility demand inferred from Mobile Phone locations. In contrast to previous methods of transit Network design, the proposed method is entirely data driven, leveraging the large-sample properties of disaggregate Mobile Phone Network data and mobility pattern mining. The method works by deriving frequent patterns of movements from anonymized Mobile Phone location data and merging them to generate candidate route designs. Additional routines for optimal route selection and service frequency setting are then employed to select a Network configuration made up of routes that maximizes systemwide traveler utility. Using data from half a million Mobile Phone users in Abidjan from the telco operator Orange, we demonstrated to provide resource-neutral system improvement of 27% in terms of end-user journey times.
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urban sensing using Mobile Phone Network data a survey of research
ACM Computing Surveys, 2015Co-Authors: Francesco Calabrese, Laura Ferrari, Vincent D BlondelAbstract:The recent development of telecommunication Networks is producing an unprecedented wealth of information and, as a consequence, an increasing interest in analyzing such data both from telecoms and from other stakeholders' points of view. In particular, Mobile Phone datasets offer access to insights into urban dynamics and human activities at an unprecedented scale and level of detail, representing a huge opportunity for research and real-world applications. This article surveys the new ideas and techniques related to the use of telecommunication data for urban sensing. We outline the data that can be collected from telecommunication Networks as well as their strengths and weaknesses with a particular focus on urban sensing. We survey existing filtering and processing techniques to extract insights from this data and summarize them to provide recommendations on which datasets and techniques to use for specific urban sensing applications. Finally, we discuss a number of challenges and open research areas currently being faced in this field. We strongly believe the material and recommendations presented here will become increasingly important as Mobile Phone Network datasets are becoming more accessible to the research community.
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Scaling behaviors in the communication Network between cities
Proceedings - 12th IEEE International Conference on Computational Science and Engineering CSE 2009, 2009Co-Authors: Gautier Krings, Francesco Calabrese, Carlo Ratti, Vincent D BlondelAbstract:Researchers have been unable to predict the large-scale features of aggregate social Networks. We analyze the anonymous communications patterns of 2.5 million customers of a Belgian Mobile Phone operator. With these communications, we construct the social Network of the customers, that we call microscopic Network. Grouping customers together by billing address city, we obtain a social Network of cities, which we call the macroscopic Network, is built from 571 towns and cities in Belgium. Using the Mobile Phone Network, we are able to show that the macroscopic Network has both a degree distribution and edge weight distribution with lognormal characteristics. We find that inter-city communications can be characterized by a gravity model: the intensity of communication between two cities is proportional to the product of the two populations divided by the square of the distance between them. Furthermore, we observe that intra-urban communications scale superlinearly with city population.
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Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network:
Environment and Planning B-planning & Design, 2009Co-Authors: Jonathan Reades, Francesco Calabrese, Carlo RattiAbstract:Several attempts have already been made to use telecommunications Networks for urban research, but the datasets employed have typically been neither dynamic nor fine grained. Against this research backdrop the Mobile Phone Network offers a compelling compromise between these extremes: it is both highly Mobile and yet still localisable in space. Moreover, the Mobile Phone’s enormous and enthusiastic adoption across most socioeconomic strata makes it a uniquely useful tool for conducting large-scale, representative behavioural research. In this paper we attempt to connect telecoms usage data from Telecom Italia Mobile (TIM) to a geography of human activity derived from data on commercial premises advertised through Pagine Gialle, the Italian ‘Yellow Pages’. We then employ eigendecomposition—a process similar to factoring but suitable for this complex dataset—to identify and extract recurring patterns of Mobile Phone usage. The resulting eigenplaces support the computational and comparative analysis of space through the lens of telecommuniations usage and enhance our understanding of the city as a ‘space of flows’.
Janne Sundell - One of the best experts on this subject based on the ideXlab platform.
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A New GPS–GS GSM-Based M-Method to Study Behavior of Brown Bears
Wildlife Society Bulletin, 2006Co-Authors: Janne Sundell, Ilpo Kojola, I HanskiAbstract:We report a new me method thod of studying brow brown bear ear (Ursus arctos arctos) behavior. ehavior. The meth method combines ombines the he technologies of Global Posit Positioning oning Systems (GPS) and Global lobal Syste ystem for or Mobi Mobile le Communicat Communication ion (GSM). A GPS–GSM collar on a bear ear locates ocates itself with the help of a GPS modul module, while the GSM module sends the locatio ocation informat nformation on to the researcher as SMS (short) me message ssage via a GSM mobil Mobile Phone Network. etwork. The collar ollar is interactive and can an receive SMS commands commands, for instance, nstance, to adjust djust the interva nterval at which location information nformation is transmitted. We tested the he method in experiments in which people equipp equipped ed with GPS–GSM Mobile Phones approached a GPS–GSM- collared bear. Spatial locations ocations of the bear ear and the he approaching person ersons are displa displayed yed on th the digital igital map on the he computer scre screen en in real-time. The dispers ispersion on of spatial information was as 2.5 m, and th the success uccess rate in the experiments was 81.2 1.2% (new spatial locations successfully received when requested). The method proved to be useful and accurate enough to study the he behavior of bears ears (e.g., escape initiation distance) istance) in the proximity of humans. We believe the methodology presen resented ted will hel help rese researchers archers to better understan understand bear ear behavior and develop strateg strategies ies to minimize inimize negative bear– human interactions. nteractions. Rapid apid data transmission creates new opportunities for anim animal al trackin tracking in gener eneral. al. We believe that the GPS mobil Mobile Phone- Phonebased based tracking will ill become the most cost-effective ost-me method thod for studying large animals nimals in areas servic serviced ed by Mobile Phone Networks. Key wo words rds behavior, brown bear, Global Positioning Systems, Global System for Mobile Communications, human contact, Ursus arctos.
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A New GPS-GSM-Based Method to Study Behavior of Brown Bears
Wildlife Society Bulletin, 2006Co-Authors: Janne Sundell, Ilpo Kojola, I HanskiAbstract:We report a new method of studying brown bear (Ursus arctos) behavior. The method combines the technologies of Global Positioning Systems (GPS) and Global System for Mobile Communication (GSM). A GPS–GSM collar on a bear locates itself with the help of a GPS module, while the GSM module sends the location information to the researcher as SMS (short) message via a GSM Mobile Phone Network. The collar is interactive and can receive SMS commands, for instance, to adjust the interval at which location information is transmitted. We tested the method in experiments in which people equipped with GPS–GSM Mobile Phones approached a GPS–GSM-collared bear. Spatial locations of the bear and the approaching persons are displayed on the digital map on the computer screen in real-time. The dispersion of spatial information was 2.5 m, and the success rate in the experiments was 81.2% (new spatial locations successfully received when requested). The method proved to be useful and accurate enough to study the behavior of bears (e.g., escape initiation distance) in the proximity of humans. We believe the methodology presented will help researchers to better understand bear behavior and develop strategies to minimize negative bear– human interactions. Rapid data transmission creates new opportunities for animal tracking in general. We believe that the GPS Mobile Phonebased tracking will become the most cost-effective method for studying large animals in areas serviced by Mobile Phone Networks.
Vincent D Blondel - One of the best experts on this subject based on the ideXlab platform.
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urban sensing using Mobile Phone Network data a survey of research
ACM Computing Surveys, 2015Co-Authors: Francesco Calabrese, Laura Ferrari, Vincent D BlondelAbstract:The recent development of telecommunication Networks is producing an unprecedented wealth of information and, as a consequence, an increasing interest in analyzing such data both from telecoms and from other stakeholders' points of view. In particular, Mobile Phone datasets offer access to insights into urban dynamics and human activities at an unprecedented scale and level of detail, representing a huge opportunity for research and real-world applications. This article surveys the new ideas and techniques related to the use of telecommunication data for urban sensing. We outline the data that can be collected from telecommunication Networks as well as their strengths and weaknesses with a particular focus on urban sensing. We survey existing filtering and processing techniques to extract insights from this data and summarize them to provide recommendations on which datasets and techniques to use for specific urban sensing applications. Finally, we discuss a number of challenges and open research areas currently being faced in this field. We strongly believe the material and recommendations presented here will become increasingly important as Mobile Phone Network datasets are becoming more accessible to the research community.
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Scaling behaviors in the communication Network between cities
Proceedings - 12th IEEE International Conference on Computational Science and Engineering CSE 2009, 2009Co-Authors: Gautier Krings, Francesco Calabrese, Carlo Ratti, Vincent D BlondelAbstract:Researchers have been unable to predict the large-scale features of aggregate social Networks. We analyze the anonymous communications patterns of 2.5 million customers of a Belgian Mobile Phone operator. With these communications, we construct the social Network of the customers, that we call microscopic Network. Grouping customers together by billing address city, we obtain a social Network of cities, which we call the macroscopic Network, is built from 571 towns and cities in Belgium. Using the Mobile Phone Network, we are able to show that the macroscopic Network has both a degree distribution and edge weight distribution with lognormal characteristics. We find that inter-city communications can be characterized by a gravity model: the intensity of communication between two cities is proportional to the product of the two populations divided by the square of the distance between them. Furthermore, we observe that intra-urban communications scale superlinearly with city population.
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Fast unfolding of communities in large Networks
Journal of Statistical Mechanics: Theory and Experiment, 2008Co-Authors: Vincent D Blondel, Jean-loup Guillaume, Renaud Lambiotte, Etienne LefebvreAbstract:We propose a simple method to extract the community structure of large Networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection method in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian Mobile Phone Network of 2.6 million customers and by analyzing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad-hoc modular Networks. .