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
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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
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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
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Dynamic People Distribution 2/2
• People counting on a set of Point of Interest
• The larger the circle the higher number of people
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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
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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
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
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
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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
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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