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VODAFONE
SMART CITIES
BIG DATA FOR DYNAMIC
PRESENCE MAPPING &
MOBILITY FLOWS
MONITORING
Sergio Gambacorta
Smart Cities Program Manager – Vodafone
Italia
Vodafone Big Data & Mobile Analytics: Italian best
practices
2
Vodafone
Dataset
NW DATA
DWH
VF-ITInternalusage
ExternalUsage
Monitoraggio del traffico di Rete:
NW Traffic Monitoring
• to enable trouble-shooting
• to plan NW infrastructures
• to improve QoS
SMART CITIES, R&D and
Commercial awarded projects
based on
• user presence mapping
• O/D matrices
• mobility flows
• traffic monitoring
Mobile Advertising &
Couponing
Opted-in Customer Base clustering to
increment advertising appeal of
Vodafone Online & Mobile inventory
Traffic and Customer
Behaviour analysis
• to optimize tariffs & promotion
• to avoid Churn and increase NPS
Location
Vodafone‘s Data Assets…
Bank Account
Credit history
Billing record
GPS
SW
BlogsBehaviour
Relationship
Address
Demographics
Machines
NFC
M2M
mobile
Payment
POS Mobile
Comm.
Mobile
Advert.
Internet
Preferences
Cars
NFC Payment
Demographics
Frequency
CouponingLogistics
3rd
Party
Data
Other
Sources
Social
Media
Market
Research
Web
APIs Web
Public
Informat.
Weather
Events
Traffic
Maps
Government
FPP
Browsing history
Household data
Crowdsourcing
Platforms
Message
Roaming
Calls
Identity
Mobile
Web
Devices
Billing
Tariffs &
Products Personal
Data
Network
Core
Vodafone
Data
Customer
service calls
Browsing history
URL
Apps
Content
TYPE
IMEI
TAC
Spend
Fraud
New
Vodafone
Data
Segment
Surveys
Reports
Search terms
3
IoT / Connected
sensors
Apps
PA Open Data
3° parties data
VF Network Data
Data Warehouse
…
… and Technical Architecture to collect and elaborate
DATA
4
NW PROBES &
TOOLS
QUANTITATIVE
LOCATION BASED
DATASET
EXTERNAL
HETEROGENEO
US DATASET
(eg. APP, Open
Data, Meters,
Sensors)
VF DWH
OPTED IN USERS
MEDIATION
LAYER
&
& ALGORITHM
PLATFORMDPI PROBES
OPTED IN USERS
External
Repository
or B.I.
Dashboard
Elaborated Datastream
Exported via Web Services,
API or SFTP
… and our «good rules» in using data
Insert Confidentiality Level in slide footer 5
PRIVACY
• Anonymization and aggregation in compliance with current
privacy norms
• Security measures in collecting, processing and storing data
TRASPARENCY
• Clear communications regarding customer data usage
• Informed consent to obtain users Opt-in and clear ways to opt-
out
VALUE
• Owned algorithms, uniqueness patents for network data
processing
• DATA enabled SOLUTIONS – NO RAW DATA supply
Projects and solutions delivered to help PAs to plan infrastructures &
services
6
Solution based on Vodafone DATA
Solution based on Data Fusion among
Vodafone DATA and external Datasets
People Count Outdoor
& services planning
on real demand
Mobility flows,
Pedestrian index,
Origin/Destination
Matrices
People Count Indoor
&
Data fusion with
sensors /video
analysis inputs
Energy, Hydric and
Gas consumption
forecasts
Emissions and waste
production forecasts
Qualitative data
fusion between
Customers Datasets
and users
Vehicular Traffic
Indicators
DRILL DOWN ON
ALGORITHMS
DEVELOPED INTERNALLY
IN SMART CITIES
PROJECTS 7
Insert Confidentiality Level on title master
Dynamic People Distribution 1/2
• Each solid is
built up from the
center of a
probed cell
• Colors from
white to red
represents
crowd level
• Map of histograms in
which the higher is the
solid, the denser is people
presence in the given city
area
12:00 am
03:00 am
Insert Confidentiality Level on title master
Dynamic People Distribution 2/2
• People counting on a set of Point of Interest
• The larger the circle the higher number of people
Insert Confidentiality Level on title master
Origin / Destination Matrices & Mobility Flows
10Presentation information in footer
• Some of the main mobility
flows between two locations
• In and Out flows from a
given location
• In - the morning
• Out - the
evening
Insert Confidentiality Level on title master
Vehicular Traffic Forecast in Close Real Time -
Heat Map
11Presentation information in footer
Free Flow
High
Congested
Impossible
Traffic Index:
User Presence Mapping in Metro Stations
Presentation information in footer
• People Count for Metro Station Red Line Green Line Green Line
Touristic flows monitoring (foreign visitors trends)
13
Foreign visitors presence by home nationalities
14
Foreign visitors segmentation by time spent / visit
repetitiveness
15
Average time spent (days) for aggregate foreign visitors Averge number of visits in the period
Foreign visitors segmentation by weekly patterns
16
SMART TOURISM e BIG DATA
COLLECTIVE
SENSING
Vodafone Italia
Foreign visitors entry points
17
C4
Touristic Flows
Monitoring
Mobility Pattern
Aggregate
Foreign Visitors
C4
Touristic Flows
Monitoring
Mobility Pattern
Aggregate
German
Visitors
C4
Touristic Flows
Monitoring
Mobility Pattern
Aggregate
Chinese
Visitors
Foreign visitors flows
21
Co-visits among different cities/areas
22
23
O/D Matrices from specific points of interest (Linate airport, Milan)
Sergio Gambacorta
Smart Cities & Big Data Program Manager
Vodafone Italy
sergio.gambacorta@vodafone.com
24
Thank you!
SUPERHUB - Synthesis
• Integration of several data sources
(e.g. PA/public transportation open
data, cellular network, etc.) to
promote sustainable multimodal
mobility• Mobile Apps for the citizen with
evolved Trip Planner and
gamification approach
• Dashboard for the PA for
infrastructures and policy planning
• Mining cellular network traffic data
to forecast road traffic, to predict
mobility patters and people
distribution
Smart
Mobility
Insert Confidentiality Level on title master
Tools
SmartC2Net - Sinthesys
• Smart Grid optimization
and monitoring through
an integrated
communication network
• Energy demand inference
based on cellular traffic
data
• Predictive models to
correlate the people
presence in a given area
with the related energy
demand
• Framework for monitoring
VODAFONE ROLE
• Geo-localized data analysis
(coming from mobile network)
• Definition and development of
algorithm to forecast energy
demand
• Heterogeneous network
Goals
Smart
Grid
Insert Confidentiality Level on title master
TOOLS
PROACTIVE - Sinthesys
• Analysis PA and Utilities
needs and infrastructures
• Heterogeneous data
processing to develop
predictive models
regarding how the users
VODAFONE ROLE
• Mobile network traffic data
collection and processing for
enabling services to increase
city safety
• Design communication network
to enable collection of data
coming from the city and the
environment
GOALS
Smart
Public
Services
• Solutions development for
more effective , efficient,
and participative
environment planning and
protection
• Monitoring the
infrastructures through
UBB mobile network,
smart sensors and
«human sensors» for
planning optimization and
environment risks
prevention

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Studying Migrations Routes: New data and Tools

  • 1. VODAFONE SMART CITIES BIG DATA FOR DYNAMIC PRESENCE MAPPING & MOBILITY FLOWS MONITORING Sergio Gambacorta Smart Cities Program Manager – Vodafone Italia
  • 2. Vodafone Big Data & Mobile Analytics: Italian best practices 2 Vodafone Dataset NW DATA DWH VF-ITInternalusage ExternalUsage Monitoraggio del traffico di Rete: NW Traffic Monitoring • to enable trouble-shooting • to plan NW infrastructures • to improve QoS SMART CITIES, R&D and Commercial awarded projects based on • user presence mapping • O/D matrices • mobility flows • traffic monitoring Mobile Advertising & Couponing Opted-in Customer Base clustering to increment advertising appeal of Vodafone Online & Mobile inventory Traffic and Customer Behaviour analysis • to optimize tariffs & promotion • to avoid Churn and increase NPS
  • 3. Location Vodafone‘s Data Assets… Bank Account Credit history Billing record GPS SW BlogsBehaviour Relationship Address Demographics Machines NFC M2M mobile Payment POS Mobile Comm. Mobile Advert. Internet Preferences Cars NFC Payment Demographics Frequency CouponingLogistics 3rd Party Data Other Sources Social Media Market Research Web APIs Web Public Informat. Weather Events Traffic Maps Government FPP Browsing history Household data Crowdsourcing Platforms Message Roaming Calls Identity Mobile Web Devices Billing Tariffs & Products Personal Data Network Core Vodafone Data Customer service calls Browsing history URL Apps Content TYPE IMEI TAC Spend Fraud New Vodafone Data Segment Surveys Reports Search terms 3 IoT / Connected sensors Apps PA Open Data 3° parties data VF Network Data Data Warehouse …
  • 4. … and Technical Architecture to collect and elaborate DATA 4 NW PROBES & TOOLS QUANTITATIVE LOCATION BASED DATASET EXTERNAL HETEROGENEO US DATASET (eg. APP, Open Data, Meters, Sensors) VF DWH OPTED IN USERS MEDIATION LAYER & & ALGORITHM PLATFORMDPI PROBES OPTED IN USERS External Repository or B.I. Dashboard Elaborated Datastream Exported via Web Services, API or SFTP
  • 5. … and our «good rules» in using data Insert Confidentiality Level in slide footer 5 PRIVACY • Anonymization and aggregation in compliance with current privacy norms • Security measures in collecting, processing and storing data TRASPARENCY • Clear communications regarding customer data usage • Informed consent to obtain users Opt-in and clear ways to opt- out VALUE • Owned algorithms, uniqueness patents for network data processing • DATA enabled SOLUTIONS – NO RAW DATA supply
  • 6. Projects and solutions delivered to help PAs to plan infrastructures & services 6 Solution based on Vodafone DATA Solution based on Data Fusion among Vodafone DATA and external Datasets People Count Outdoor & services planning on real demand Mobility flows, Pedestrian index, Origin/Destination Matrices People Count Indoor & Data fusion with sensors /video analysis inputs Energy, Hydric and Gas consumption forecasts Emissions and waste production forecasts Qualitative data fusion between Customers Datasets and users Vehicular Traffic Indicators
  • 7. DRILL DOWN ON ALGORITHMS DEVELOPED INTERNALLY IN SMART CITIES PROJECTS 7
  • 8. Insert Confidentiality Level on title master Dynamic People Distribution 1/2 • Each solid is built up from the center of a probed cell • Colors from white to red represents crowd level • Map of histograms in which the higher is the solid, the denser is people presence in the given city area 12:00 am 03:00 am
  • 9. Insert Confidentiality Level on title master Dynamic People Distribution 2/2 • People counting on a set of Point of Interest • The larger the circle the higher number of people
  • 10. Insert Confidentiality Level on title master Origin / Destination Matrices & Mobility Flows 10Presentation information in footer • Some of the main mobility flows between two locations • In and Out flows from a given location • In - the morning • Out - the evening
  • 11. Insert Confidentiality Level on title master Vehicular Traffic Forecast in Close Real Time - Heat Map 11Presentation information in footer Free Flow High Congested Impossible Traffic Index:
  • 12. User Presence Mapping in Metro Stations Presentation information in footer • People Count for Metro Station Red Line Green Line Green Line
  • 13. Touristic flows monitoring (foreign visitors trends) 13
  • 14. Foreign visitors presence by home nationalities 14
  • 15. Foreign visitors segmentation by time spent / visit repetitiveness 15 Average time spent (days) for aggregate foreign visitors Averge number of visits in the period
  • 16. Foreign visitors segmentation by weekly patterns 16
  • 17. SMART TOURISM e BIG DATA COLLECTIVE SENSING Vodafone Italia Foreign visitors entry points 17
  • 22. Co-visits among different cities/areas 22
  • 23. 23 O/D Matrices from specific points of interest (Linate airport, Milan)
  • 24. Sergio Gambacorta Smart Cities & Big Data Program Manager Vodafone Italy sergio.gambacorta@vodafone.com 24 Thank you!
  • 25. SUPERHUB - Synthesis • Integration of several data sources (e.g. PA/public transportation open data, cellular network, etc.) to promote sustainable multimodal mobility• Mobile Apps for the citizen with evolved Trip Planner and gamification approach • Dashboard for the PA for infrastructures and policy planning • Mining cellular network traffic data to forecast road traffic, to predict mobility patters and people distribution Smart Mobility
  • 26. Insert Confidentiality Level on title master Tools SmartC2Net - Sinthesys • Smart Grid optimization and monitoring through an integrated communication network • Energy demand inference based on cellular traffic data • Predictive models to correlate the people presence in a given area with the related energy demand • Framework for monitoring VODAFONE ROLE • Geo-localized data analysis (coming from mobile network) • Definition and development of algorithm to forecast energy demand • Heterogeneous network Goals Smart Grid
  • 27. Insert Confidentiality Level on title master TOOLS PROACTIVE - Sinthesys • Analysis PA and Utilities needs and infrastructures • Heterogeneous data processing to develop predictive models regarding how the users VODAFONE ROLE • Mobile network traffic data collection and processing for enabling services to increase city safety • Design communication network to enable collection of data coming from the city and the environment GOALS Smart Public Services • Solutions development for more effective , efficient, and participative environment planning and protection • Monitoring the infrastructures through UBB mobile network, smart sensors and «human sensors» for planning optimization and environment risks prevention