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Monitoring temporary populations through cellular core network data


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Monitoring temporary populations through cellular core network data
Fabio Manfredini, Paolo Tagliolato, Carmelo di Rosa - Department of Architecture and Planning, Polytechnic of Milan

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Monitoring temporary populations through cellular core network data

  1. 1. Monitoring visitors and tourists through cellular core network data Fabio Manfredini , Paolo Tagliolato, Carmelo Di Rosa Laboratorio Analisi Dati e Cartografia Dipartimento di Architettura e Pianificazione, Politecnico di Milano ICCSA 2011 CTP Workshop Santander 19 – 22 October 2011
  2. 2. The research has been carried out by the Department of Architecture and Planning of the Politecnico di Milano for Telecom Italia, the main Italian mobile phone operator. The aim was to assess the contribution of cellular phone traffic data for understanding and analyzing urban dynamics and to propose possible uses of this kind of information in urban analysis. The coherence with traditional data source has been tested in order to verify the reliability of mobile data in describing city use and patterns. The work was coordinated by Fabio Manfredini and Paola Pucci Paolo Tagliolato, Paolo Dilda, Paolo Beria, Carmelo Di Rosa and Eugenio Morello participated in the research. Outline of the research
  3. 3. Mobile phone data analysis – un-volonteered geography Data Research area Purpose Tracks of calls of individual phone users (active mobile positioning) Network science Study of geometrical patterns of the mobility of individuals (deprived of the specific geographical reference) Spatial distribution of cell phone network traffic intensity (derived from cellular network log files) Mobile landscapes Study of the density of use of a territory Spatial and temporal distribution of GSM active clients – switched on mobile phone Monitoring tourists and visitors
  4. 4. MICRO Scale MACRO Scale Monitoring the Milan International Design Week Erlang data Urban sections <ul><li>Social housing Residential neighbours </li></ul><ul><li>- Residential neighbours </li></ul><ul><li>Commercial centres </li></ul><ul><li>Factories </li></ul><ul><li>Urban sprawl area </li></ul><ul><li>Railway stations </li></ul><ul><li>Dense urban fabric </li></ul><ul><li>university </li></ul>Erlang data Handover MSC active clients Aim: correlate mobile phone data with statistical data at the municipal scale Municipal scale <ul><li>residential density </li></ul><ul><li>employed density </li></ul><ul><li>daily population </li></ul><ul><li>… . </li></ul>Statistical indicators GIS layers <ul><li>Land Use / Land Cover </li></ul><ul><li>Activities distribution </li></ul>MACRO SCALE Which applications of mobile phone data at the macro scale? MICRO SCALE What can we learn from mobile phone data? Are the Erlang trends compatible with actual knowledge on urban dynamics and on urban practices? A multiscale approach
  5. 5. A few questions <ul><li>Which is the reliability of mobile phone data analysis compared to traditional data source? </li></ul><ul><li>Traditional data survey are expansive and not updated. </li></ul><ul><li>They are not able to describe adequatly practices and dynamics of the contemporary cities (mobility, trends in daily and seasonal popolation, etc.) </li></ul><ul><li>How can we interpret spatial and temporal patterns of mobile phone use density from a urban perspective? </li></ul><ul><li>Where occur anomalies? where concentrates activity? </li></ul><ul><li>When? For which reason? </li></ul><ul><li>Are mobile phone data useful for Urban Analysis? </li></ul><ul><li>Which applications of these data for public administrations? </li></ul><ul><li>Which is the mobile data “added value” in knowledge for urban actors respect to traditional data sources? </li></ul><ul><li>Is it possible to monitor tourists and visitors (temporary populations)? </li></ul>
  6. 6. Micro scale analysis Selected Urban Contexts <ul><ul><li>Different profiles for different railway stations </li></ul></ul><ul><ul><li>(Compatibility of Erlang trends with the rhythm of the city) </li></ul></ul>sundays weekdays
  7. 7. Spatial and temporal patterns during the 2009 Int. Design Week The special event Typical weekday Special event / Typical weekday ratio Nightime / Daytime ratio Interpretation of spatial and temporal patterns is a crucial task.
  8. 8. Mobile switching center (MSC), is the primary service delivery node for GSM, responsible for routing voice calls and SMS. It also records information on the mobility of subscribers by updating the position of mobile devices in the HLR (Home Location Register), which contains all subscriber information. GSM architecture
  9. 9. <ul><li>We used data on switched on mobile phone rather than on mobile phone traffic (calls received or made). </li></ul><ul><li>We know that the pervasivity of mobile phone is over 100% in the majority of European countries but we are also aware that mobile phone usage heavily depends on social and age characteristics of mobile phone users. </li></ul><ul><li>The data at our disposal were, for every hour the two time periods considered (September 2009, April 2010), the number of GSM active clients for each of the Lombardia region MSC Service Area, distinguished by the nationality of the SIM. </li></ul>Mobile Switch Center (MSC) data
  10. 10. MSC Service areas Map of the Lombardia region’s MSC Service Area Zoom on the Milano Urban region Statistics for the Lombardia region MSC service areas (square Km) The service area of each MSC has a variable size depending on the number of GSM tower cells served and on the intensity of mobile phone traffic generated inside it. Average 1591,988658 Median 772,2885667 Standard deviation 2148,758884 Interval 7586,93098 Min 27,43751191 Max 7614,368492 Number 15
  11. 11. Hourly Active clients working day – Saturday ratio in the MSC service area central Milan (7/9/2009 – 20/9/2009) Daily Milan city rithms – September 2009 <ul><li>Measuring urban attractivity </li></ul><ul><li>during working days, the city of Milan attracts a large amount of people from a vast territory that goes beyond the municipal boundaries, namely Milan Urban region . </li></ul><ul><li>the ratio Wednesday / Saturday sharply increases in Milan during the first hours of the day until 8 AM (marked in black). Afterwards, the amount of contacts is steady. After 4 PM the number of active clients decreases very slowly, until it reaches the same value of the morning. </li></ul><ul><li>The number of contacts during Wednesday is more than a half than that of Saturdays. </li></ul><ul><li>Milan municipality’s official data inform that each working day almost 600.000 people enter in Milan, a value that is compatible with what emerges from MSC service area statistics. </li></ul>
  12. 12. Monthly Milan city rithms – April 2010 Week-end Easter 2010 hourly variation of active clients in Milan MSC service area for the period April, 1st 2010 – April, 30th 2010.
  13. 13. <ul><li>different temporal patterns of daily population: </li></ul><ul><li>Working days vs week-end days </li></ul><ul><li>Easter vs holidays </li></ul><ul><li>huge decrease of active clients during the weekend, in particular on Saturday and on Sunday due to the reduction of job and study travels. </li></ul><ul><li>the Eastern period, Saturday and Monday April 4 – 5, presents an inflection even more pronounced than that of other April weekends. In this case there is a significant reduction of active clients, related to the long Eastern weekend, when many inhabitants of Milan leave the city. </li></ul><ul><li>At Eastern Sunday, active clients are about one third less than in the subsequent Sunday. </li></ul>The possibility to obtain an indirect measure of the temporal variation of presences in the city is a great value of this data, relevant for policy and decision makers. Monthly Milan city rithms – April 2010
  14. 14. MSC active clients vs foreign residents The 10 most numerous nationality in the Lombardia Region from 2009 official statistics (left) and from MSC Register during the September 7 – 21, 2009 period (right) Nationality Percentage (active clients) German 22.9% Swiss 15.1% English 6.9% French 6.4% Romanian 5.9% Polish 5.8% Spanish 4.3% Dutch 2.7% Czech Republic 2.2% Austrian 2.1% Nationality Percentage (residents) Romanian 35.5% Moroccan 29.5% Albanian 27.1% Egiptian 15.9% Filipina 12.3% Chinese 11.3% Indian 11.1% Ecuador 10.8% Peruvian 10.0% Ucrain 8.7%
  15. 15. Statistics on the occupancy of collective tourist accommodation refer to the number of arrivals (at accommodation establishments) and the number of nights spent by residents and non-residents, separated into establishment type or region; annual and monthly statistical series are available. This information is available at the provincial spatial scale and underestimates the dimension of phenomena, because it considers only tourists or visitors who go to official structures. A large proportion of temporary visitors are therefore excluded . there are about 500,000 visitors per year who are not counted by statistics because they spend nights by friends or by informal touristic structures (Observatory of Tourism – Milan). Tourism statistic
  16. 16. Escludendo le SIM Italiane si evidenziano due eventi. Pasqua: 4-5 aprile; Salone del mobile: 14-19 aprile (64% in più della media degli altri giorni di aprile) Foreign active clients during April 2010 Int. Design week Easter 2010 Garda Lake MSC Milano MSC
  17. 17. Foreign active clients during the 2010 International Design Week
  18. 18. Foreign active clients during the 2010 International Design Week: most numerous nationalities Nationality Percentage % French 9,8% Swiss 9,2% United Kingdom 8,7% Spain 8,0% German 7,5% Russian Federation 5,6% USA 4,0%
  19. 19. Despite of the dimension of the MSC service area, the data were able to catch the foreign trends as a phenomenon visible at a urban scale. For major events, active clients can provide an important tool for monitoring visitors and tourists, for evaluating the attractiveness of a big event, for evaluating its economic impact and for providing new touristic and business services directed to specific nationalities. There is a strong need of updated knowledge on urban attractiveness, a major component of global cities competition which is hardly intercepted by standard surveys. Innovative methods are therefore required for measuring and monitoring tourists and visitors at the different urban scales. MSC active clients data seems to be promising for visitors and tourist monitoring because it provides information that currently institutional sources do not offer. Conclusion
  20. 20. This study suggests that cell-phone-network data, due to their temporal and spatial resolution, has the potential to drastically change the way we view and understand the urban environment and the urban populations . Mobile phone data analysis is a multidisciplinary topic: data mining techniques, representation, programming, network analysis, urban analysis are some of the components of this “new” scientific field. We collected ideas and proposals from public and private bodies on possible applications of this approach to different topics such as event management, civil protection, mobility monitoring, urban rhythms analysis and mapping . Conclusion
  21. 21. Thank you! [email_address]