“New Technologies in Smart Mobil ity”ANALYT ICS FOR RA IL

C R E AT I N G V A L U E F R O M M A C H I N E - D R I V E N B I G D ATA

Fa b i o l a B e r m e j oB u s i n e s s D e v e l o p m e n t D i r e c t o r , A l t r a n E s p a ñ a

f a b i o l a . b e r m e j o @ a l t r a n . c o m

RailBcn2015

RailBcn2015

“Industrial Revolution ( XIX c.)”

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New Technologies for future mobility

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Do you know…?

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45% of all companies would like to use their data – but do not have the abilities

Vueforgetm is our overall concept to create value from machine-driven Big Data

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35% of all companies do not understand big data technologies

40% of all companies fear technical problems for their IT

41% want to run analytics for decision support,33% to help forecasting and 37% to optimize resource planning

Only 27% already run big data analytics – but 96% see big data analytics as relevant

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CASES OF USES

CUSTOMER ENGAGEMENT

PREDICTIVE MAINTENANCE

UBIQUITOUS REAL TIME RAILWAY MONITORING

1 2 3

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To Adapt the offer to satisfy the demand taking into account the efficiency in: ECONOMIC / SOCIAL / ENVIRONMENTAL / TECHNICAL

USE CASE: CUSTOMER ENGAGEMENT.

For the purpose of faster multi-modal transport system, passengers need know how and when to change transport system from railways to shared vehicles, buses, etc. All these mixed with incident info.

NEE

D F

OR

REAL

TI

ME

INFO

RMAT

ION

How can we get to my

destination? Will I get there

on time?

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Adquisition of Tickets Experience during the journey

Experience in the station First change

FOCUS ON RAILWAY:SMART MOBILITY

The dream starts before the journey

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INTERMODAL TRANSPORTAnalysis of citizens behaviour and intermodal transport

› To Understand citizen behaviour as the driver to improve the services and to generate new needs.

› Sustainability, security and efficiency for transport. Ecological models of transport, cleaner city tours. Recommendations.

› Improving inter-modality of people and goods.

› Control and management of mass events.

› Intermodal transport during the journey from point of origin to destination (limited by filters)

› Categorize user activities related to personal mobility and transport means.

› KPI GIS Measure Speed, noise contamination, temperature, Humidity, air pressure to obtain a mobility matrix.

› Build statistic dashboards & interactive web maps thru VF Think backend. Big data insight services. Anonymized Data.

› Use Altran's unique low power, 24/7 positioning system with GPS precision.

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CASES OF USES

CUSTOMER ENGAGEMENT

PREDICTIVE MAINTENANCE

UBIQUITOUS REAL TIME RAILWAY MONITORING

1 2 3

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INTRODUCCIÓN. DISRUPTIVE OPPORTUNITYMonitoring & Predictive Maintenance

2 3PREDICTIVE ANALYSIS UBIQUITOUS REAL TIME

MONITORING

Predictive maintenance using big data analytics by gathering sensor data in real time is one of the key areas of focus. This facilitates productivity in infrastructure, and vehicle maintenance process through proactive steps. Between these steps we can find:› Predictive Maintenance› Predictive Spare parts allocation› Predictive Supply Chain by

intelligent suppliers collaboration

Automatic monitoring of railway engines, and carriages, infrastructure (catenary, tracks, etc) and facilities operations with real-time notification of any faults or interruption of process at any place via smart phone applications help managers get information any time seamlessly.

› Aggregated car monitoring classified by:› Model› Engine

› Aggregated car monitoring:› Speed› Fuel Consumption› Oil› Acceleration› Brakes

› Aggregated view of trips› Send messages to all vehicles, or some of

them› Content management:

› Advices› Alerts› Games - competition

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› Trips tracking› Car sensor monitoring and alerts

› Speed› Fuel consumption› Oil› Acceleration› Brakes

› Alerts:› Commercial› Factory failure detection› Driving best practices

› Gamification - Competition:› Best driver› Less fuel consumption› Best routes

Car Owner

Car OEM

USE CASE 2: Monitoring & Predictive Maintenance. From Connected Vehicle to Connected Railway

.

Analytics(Big

Data)

Business

Users

Insights-Value

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SUMMARY: NEW TECHNOLOGIES FOR SMART MOBILITY

ANALYT ICS FOR RA ILC R E AT I N G V A L U E F R O M

M A C H I N E - D R I V E N B I G D ATA

Fa b i o l a B e r m e j oB u s i n e s s D e v e l o p m e n t D i r e c t o r , A l t r a n E s p a ñ a

f a b i o l a . b e r m e j o @ a l t r a n . c o m