2013
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Pisa tourism fluxes observatory: deriving mobility indicators from GSM calls habits
Furletti B., Gabrielli L., Rinzivillo S., Renso C.
The necessity to improve the management of the resources, urged many local governments to adhere to European initiatives in the context of competitiveness and sustainability, for creating the right balance between the welfare of tourists, the needs of the natural and cultural environment and the development and competitiveness of destinations and businesses. For many Italian Municipalities, this requirements become concrete with the establishment of a tourism monitoring systems that aims at survey these phenomenon through the analysis of heterogeneous data ranging from information of the territory, energy consumption, use of the land, and linked data (arrival and departure from the airport, bus, hotels etc). We describe the permanent observatory of touristic fluxes we realized in the town of Pisa where the standard indicators have been extended with an indicator of people presence extracted from mobile GSM call data and other exploratory analyses made by using the mobile phone data.we developed a method to partition the users into residents, commuters, in transit and visitors starting from a spatio-temporal profile inferred from people call habits.Source: NetMob 2013 - Third International Conference on the Analysis of Mobile Phone Datasets, pp. 107–109, MIT Media Lab, Cambridge, MA, 1-3 Maggio 2013
Furletti B., Gabrielli L., Rinzivillo S., Renso C.
The necessity to improve the management of the resources, urged many local governments to adhere to European initiatives in the context of competitiveness and sustainability, for creating the right balance between the welfare of tourists, the needs of the natural and cultural environment and the development and competitiveness of destinations and businesses. For many Italian Municipalities, this requirements become concrete with the establishment of a tourism monitoring systems that aims at survey these phenomenon through the analysis of heterogeneous data ranging from information of the territory, energy consumption, use of the land, and linked data (arrival and departure from the airport, bus, hotels etc). We describe the permanent observatory of touristic fluxes we realized in the town of Pisa where the standard indicators have been extended with an indicator of people presence extracted from mobile GSM call data and other exploratory analyses made by using the mobile phone data.we developed a method to partition the users into residents, commuters, in transit and visitors starting from a spatio-temporal profile inferred from people call habits.Source: NetMob 2013 - Third International Conference on the Analysis of Mobile Phone Datasets, pp. 107–109, MIT Media Lab, Cambridge, MA, 1-3 Maggio 2013
See at:
perso.uclouvain.be 
| CNR ExploRA
2013
Conference article
Unknown
Where have you been today? Annotating trajectories with DayTag
Rinzivillo S., De Lucca Siqueira F., Gabrielli L., Renso C.
Traditionally, the information about human mobility behav- ior, called diary, is acquired from volunteers by means of paper-and- pencil surveys. These diaries, representing the mobile activities of indi- viduals, are semantically rich, but lack in spatial and temporal precision. An alternative way is collecting diaries by annotating with activities the GPS tracks of individuals. This is more accurate from a spatio-temporal point of view, but the manual annotation becomes a burdensome work for the user. The tool we propose, called DayTag, is designed as a per- sonal assistant to help an individual to reconstruct her/his diary from the GPS tracks collected by a smartphone. The user interacts through the software to visualize and annotate the trajectories, thus resulting in a simple way to get user diaries.Source: SSTD 2013 - Advances in Spatial and Temporal Databases. 13th International Symposium, pp. 467–471, Munich, Germany, 21-23 August 2013
Project(s): SEEK
Rinzivillo S., De Lucca Siqueira F., Gabrielli L., Renso C.
Traditionally, the information about human mobility behav- ior, called diary, is acquired from volunteers by means of paper-and- pencil surveys. These diaries, representing the mobile activities of indi- viduals, are semantically rich, but lack in spatial and temporal precision. An alternative way is collecting diaries by annotating with activities the GPS tracks of individuals. This is more accurate from a spatio-temporal point of view, but the manual annotation becomes a burdensome work for the user. The tool we propose, called DayTag, is designed as a per- sonal assistant to help an individual to reconstruct her/his diary from the GPS tracks collected by a smartphone. The user interacts through the software to visualize and annotate the trajectories, thus resulting in a simple way to get user diaries.Source: SSTD 2013 - Advances in Spatial and Temporal Databases. 13th International Symposium, pp. 467–471, Munich, Germany, 21-23 August 2013
Project(s): SEEK
See at: CNR ExploRA
2013
Conference article
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Analysis of GSM calls data for understanding user mobility behavior
Furletti B., Gabrielli L., Renso C., Rinzivillo S.
This information about our GSM calls is stored by the TelCo operator in large volumes and with strict privacy constraints making it challenging the analysis of these fingerprints for inferring mobility behavior. This paper proposes a strategy for mobility behavior identification based on aggregated calling profiles of mobile phone users. This compact representation of the user call profiles is the input of the mining algorithm for automatically classifying various kinds of mobility behavior. A further advantage of having defined the call profiles is that the analysis phase is based on summarized privacy-preserving representation of the original data. We show how these call profiles permit to design a two step process - implemented into a system - based on a bootstrap phase and a running phase for classifying users into behavior categories. We evaluated the system in two case studies where individuals are classified into residents, commuters and visitors. We conclude the paper with a discussion which emphasizes the role of the call profiles for the design of a new collaboration model between data provider and data analyst.Source: Big Data 2013 - 2013 IEEE International Conference on Big Data, pp. 550–555, Santa Clara Marriott, CA, USA, 6-9 October 2013
DOI: 10.1109/bigdata.2013.6691621
Project(s): DATA SIM
Metrics:
Furletti B., Gabrielli L., Renso C., Rinzivillo S.
This information about our GSM calls is stored by the TelCo operator in large volumes and with strict privacy constraints making it challenging the analysis of these fingerprints for inferring mobility behavior. This paper proposes a strategy for mobility behavior identification based on aggregated calling profiles of mobile phone users. This compact representation of the user call profiles is the input of the mining algorithm for automatically classifying various kinds of mobility behavior. A further advantage of having defined the call profiles is that the analysis phase is based on summarized privacy-preserving representation of the original data. We show how these call profiles permit to design a two step process - implemented into a system - based on a bootstrap phase and a running phase for classifying users into behavior categories. We evaluated the system in two case studies where individuals are classified into residents, commuters and visitors. We conclude the paper with a discussion which emphasizes the role of the call profiles for the design of a new collaboration model between data provider and data analyst.Source: Big Data 2013 - 2013 IEEE International Conference on Big Data, pp. 550–555, Santa Clara Marriott, CA, USA, 6-9 October 2013
DOI: 10.1109/bigdata.2013.6691621
Project(s): DATA SIM
Metrics:
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doi.org | ieeexplore.ieee.org | CNR ExploRA
2013
Conference article
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MP4A project: mobility planning for Africa
Nanni M., Trasarti R., Furletti B., Gabrielli L., Van Der Mede P., De Bruijn J., De Romph E., Bruil G.
This project aims to create a tool that uses mobile phone transaction (trajectory) data that will be able to address transportation related challenges, thus allowing promotion and facilitation of sustainable urban mobility planning in Third World countries. The proposed tool is a transport demand model for Ivory Coast, with emphasis on its major urbanization Abidjan. The consortium will bring together available data from the internet, and integrate these with the mobility data obtained from the mobile phones in order to build the best possible transport model. A transport model allows an understanding of current and future infrastructure requirements in Ivory Coast. As such, this project will provide the first proof of concept. In this context, long-term analysis of individual call traces will be performed to reconstruct systematic movements, and to infer an origin-destination matrix. A similar process will be performed using the locations of caller and recipient of phone calls, enabling the comparison of socio-economic ties vs. mobility. The emerging links between different areas will be used to build an effective map to optimize regional border definitions and road infrastructure from a mobility perspective. Finally, we will try to build specialized origin-destination matrices for specific categories of population. Such categories will be inferred from data through analysis of calling behaviours, and will also be used to characterize the population of different cities. The project also includes a study of data compliance with distributions of standard measures observed in literature, including distribution of calls, call durations and call network features.Source: Data for Development - Special session of the Third International Conference on the Analysis of Mobile Phone Datasets, Cambridge, USA, 2-3 May 2013
Nanni M., Trasarti R., Furletti B., Gabrielli L., Van Der Mede P., De Bruijn J., De Romph E., Bruil G.
This project aims to create a tool that uses mobile phone transaction (trajectory) data that will be able to address transportation related challenges, thus allowing promotion and facilitation of sustainable urban mobility planning in Third World countries. The proposed tool is a transport demand model for Ivory Coast, with emphasis on its major urbanization Abidjan. The consortium will bring together available data from the internet, and integrate these with the mobility data obtained from the mobile phones in order to build the best possible transport model. A transport model allows an understanding of current and future infrastructure requirements in Ivory Coast. As such, this project will provide the first proof of concept. In this context, long-term analysis of individual call traces will be performed to reconstruct systematic movements, and to infer an origin-destination matrix. A similar process will be performed using the locations of caller and recipient of phone calls, enabling the comparison of socio-economic ties vs. mobility. The emerging links between different areas will be used to build an effective map to optimize regional border definitions and road infrastructure from a mobility perspective. Finally, we will try to build specialized origin-destination matrices for specific categories of population. Such categories will be inferred from data through analysis of calling behaviours, and will also be used to characterize the population of different cities. The project also includes a study of data compliance with distributions of standard measures observed in literature, including distribution of calls, call durations and call network features.Source: Data for Development - Special session of the Third International Conference on the Analysis of Mobile Phone Datasets, Cambridge, USA, 2-3 May 2013
See at:
perso.uclouvain.be | CNR ExploRA