MOBILE PHONE DATA The core data model and location of events Roberta Radini Istat

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1 MOBILE PHONE DATA Roberta Radini Istat WP5 Essnet on BD Madrid, 20st March 2018 Joint work with: Istat team: Fabrizio De Fausti Tiziana Tuoto Luca Valentino

2 Outline Description the Best Service Area: Spatial distribution Information Aggregation Process of CDRs with the BSAs Concluding remarks and next steps 2

3 Supply of CDRs ISTAT received CDR data from WIND-TRE at the end of February 2017 CDRs refer to calls and SMS (text messages) in the province of Pisa in the period between 1 st January and 12 th February. The record path of the CDRs contained in the files: Variables names TIPOLOGIA_CDR: CHIAVE_NUM_CHIAMANTE: DATA_INIZIO_CHIAMATA: ORA_INIZIO_CHIAMATA: DURATA_CHIAMATA: COD_MUNIC: COD_CELL: Descriptions Call or SMS Code of SIM The date of the beginning of the call The time of the beginning of the call The duration of the call The municipality Code Cell or Cod Sector Description of compiled mobile phone data sets 3

4 Spatial distribution The CDRs contain the cell id or sector id of the cell that made the connection to the Network The size of the area covered by each sector of the antenna (called Best Service Area) depends from, as seen: the density of potential users, morphology of the territory and the antenna technology Tecnology Frequency (MHz) Cell radius (km) Cell area (km 2 ) Relative Cell Count Dual 1G GSM 2G GSM 2G UMTS 3G LTE cells can have a radius of up to 100 km and support the communication of terminals that move at a speed of 350 Km/h UMTS and LTE cells are often, but not always, located at the same site as GSM cells. 4

5 Examples of the BSAs of 3 antennas We can see only BSAs of 3G and 4G because the area of 2G and 3G are overlapping, but the 2G technology serves the old generation devices (no Smartphone) Spatial distribution Note that the potition of the tower of antenna is in a specific municipality (red border) while the BSAs cover several Municipalities 4G 3G 5

6 Sector_id Cod Antenna Best Service Area Information Cod Munic. Municipality BSAs are characterized by a unique identifier and a shape file. Elaborating the shape file with ARCGIS it is possible to calculate: the area municipality (A municipality), the area BSA (A cell ) and percentage of overlap (BSA_FRACT) between the BSA and the area of the municipalities A municipality A cell BSA_FRACT(cell, municipality) = X 100 A cell Overlapping AREA BSA_FRACT % type genetation Date extraction MM_AA Pisa , ,9538 2G 02_ San Giuliano Terme 34681, ,4603 2G 02_ Cascina ,306 84,5859 2G 02_ Pisa , ,2421 2G 02_ San Giuliano Terme 13150, , G 02_ Cascina ,378 81,1734 2G 02_ Pisa ,644 99,9994 2G 02_ Cascina 7, , G 02_17 San Giuliano Terme PISA Sector_id: Sector_id: Sector_id: Cascina 6

7 Sector_id Cod Antenna Cod Municip. Best Service Area Information municipality AREA overlapping BSS_FRACT type % genetation Date extraction MM_AA San Giuliano Terme 1103, , G 02_ Cascina , , G 02_ Pisa , , G 02_ San Giuliano Terme 54361, , G 02_ Cascina ,333 78, G 02_ Pisa ,75 99, G 02_ Pisa ,708 23, G 02_ San Giuliano Terme 60894, , G 02_ Cascina ,459 73, G 02_ Pisa , , G 02_ San Giuliano Terme ,7469 San 22, Giuliano Terme 3G 02_ Cascina , , G 02_ Pisa , , G 02_17 7

8 Aggregation process of CDRs with the BSAs 8

9 Concluding remarks and next steps The actual interpolation takes place during the construction of the basic data set and has no information on the geographical position but only an administrative position (i.e. Municipality). This operation should be carried out by the MNOs and represents a specification of privacy preserving by design The extraction of CDRs and BSAs must be at the same time, because the network changes, coverage areas change, new antennae are added and existing antennae are removed. As described in the Deliverable 5.3, section 3.2, this approach allows direct interpolation from coverage areas to lowest level local administrative units using an area proportion In the described approach we assumed that the calls distribution was uniform on the cell area. The next step, for us, is to integrate land use information to get a non-uniform distribution of calls 9