Tecnologie miniaturizzate a basso costo, basso consumo energetico, basso costo di connettività: stanno invadendo il nostro quotidiano in tutti gli ambiti di settore: Ambiente, Salute, Trasporti, Industria.... Proviamo a capire quali sono i casi di Business che stanno funzionando, quali i modelli di utilizzo implementati e quali le tecnologie abilitanti. Infine capiamo come Oracle aiuta i suoi clienti a cogliere questa opportunità attraverso le sue tecnologie.

1. Nino Guarnacci
Solu-on Architect IoT & Mobile
nino.guarnacci@oracle.com

2. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Agenda
§ Context
§ Architecture
§ Use-Cases
§ Demo
2

3. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
People & Apps
Processes
Step 3Step 3Step 2Step 1
Data & Analysis
Physical Devices and Objects
Connected to the Internet and
Each Other for Intelligent
Decision Making Delivering the Right Informa>on to the Right
Person (or Machine) at the Right Time
Leveraging Data into Useful
Informa>on for Decision Making
Connec>ng People in More
Relevant, Valuable Ways
What is the Internet of Things

4. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Confiden>al – Oracle 4
IoT is enabling new business models..
Break / Fix
or Scheduled
Predic-ve
Prescrip-ve
Ownership As a Service
Sta-c
Analy-cs
Real-Time
Big-Data
Analy-cs
Central
Service
Self-Serve /
Self-Guided
Service
Maintenance
Business Analy>cs Service
Consump>on Model

5. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
IoT drives Industrial Innova>on (I)
5
Healthcare
• Remote healthcare asset
management and enable
self-service
• Monitor pa>ent behavior
in real->me
Consumer Products
• Proac>ve remote
maintenance and service
• Replacement supply
tracker
• Consumer habits tracking
Manufacturing
• Sensors track products
across supply chains
• Improve Inventory
Management
• Reduce logis>cal costs and
capital expenditure
Oil & Gas / U-li-es
• Automa>on, control and
monitoring of pipelines, oil
tanks
• Asset tracking

6. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
IoT drives Industrial Innova>on (II)
6
Public sector
• Waste management
• Traffic management
• City automa>on
(parking, ...)
Banking & Insurance
• Usage-based insurance
• New POS
• Fraud detec>on and
asset recovery
Retail
• Shopping analy>cs
• Vending machine remote
controlling
• Improve Inventory
Management
• Digital Signage
Real estate / Domo-cs
• Smart ligh>ng
• Asset control, monitoring
and automa>on
• Access & physical security
improvement
• HVAC automa>on

7. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
IoT drives Industrial Innova>on (III)
7
Logis-cs
• Asset tracking
• Flows op>miza>on
• Supply chain automa>on
Agriculture
• Livestock tracking
• Irriga>on
• Supply chain automa>on
Many other industries / subindustries impacted in
core and non-core processes

8. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
San Francisco Parking
• The global first implementa>on of a city
wide “smart” parking management system
and technology to manage parking supply
and demand more intelligently.
• “We have sensors at 8,200 of the city’s
27,000 metered parking spaces, and we
get informa>on from the gate arms at the
city’s 14 garages, which among them have
about 13,000 spaces
Smart City: Parking Management
8

9. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Agenda
§ Context
§ Architecture
§ Use-Cases
§ Demo
9

10. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
• Beger Customer Experience
• New Business Models
• Opera>onal Improvements
• Increased Efficiency
Grow
Revenue
Reduce
Cost
2 main Business Benefits pillars driving IoT adop>on
• HVAC
• Ligh>ng
• Safety and Security
• Resource U>liza>on
• Maintenance
• Preventa>ve Maintenance
• Remote Diagnos>cs
• Safety Systems
• V2X and C2X
• Fleet and Use Management
Shareholder
Value

11. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Reward
Info &
Decision
Making
Facilita>on
Service &
Innova>on
Reward
Information &
Decision Making
Facilitation Innovation

12. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
REWARD CONSUMERS FOR THEIR TIME,
MONEY, EFFORT, AND ENGAGEMENT
PactApp provides a service to businesses in which
employees enrolled in the company’s health plan
commit to a certain number of ac>ve days per
week, and are subsequently rewarded (or
punished) for each day they meet their goals (or
don’t).
Through loca>on-based check-in tracker–-based
logging, aims to lower (or raise!) deduc>bles with
each workout by $5.
Reward
Promo>onal rewards in the form of
coupons, discounts, or deals
Promotion
Gamifica>on rewards customers based on
contextual elements
Gamification
Brands can use sensors to reward consumers
by entertaining them
Entertainment

13. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
EMPOWER CONSUMERS WITH THE ABILITY
TO ACCESS AND ACT ON INTELLIGENCE
Whirlpool unveiled connected washers
and dryers that monitor product
performance data to drive e cliency.
Appliances are integrated with the Nest
thermostat which, if set to Away,
ac>vates an Ecoboost to longer drying
>mes at a lower temperature to
conserve energy.
Owners can access the appliance’s
remotely via their mobile device.
Information &
Decision Making
Content that aids in product and service
evalua>on.
Evaluation
Loca>on-based aid, typically delivered as naviga>on
or way-finding
Navigation
Monitoring capabili>es added to things people
care about
Monitoring
News or informa>on provided by sensors for public
awareness.
News

14. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
FOSTER EASIER, MORE ACCESSIBLE, AND
CONVENIENT BRAND EXPERIENCES
Starbucks now makes transac>ons
possible beyond the Starbucks app
through third-party integra>ons
(extending beyond smartphones) with
wearable devices such as Microson Band,
Samsung’s Galaxy Gear, and Pebble.
By integra>ng with na>ve payment apps,
for instance, customers are able to pay
for their beverages via the wearable.
Facilitation
IoT expands conversion capabili>es through the
purchase funnel
Conversation
IoT helps brands make their products and services
more useful.
Utility
Iden>ty authen>ca>on through sensor data facilitates
faster valida>on or admission process
Identity
IoT is shining how brands facilitate customer
experience via the payment process
Payment

15. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
SUPPORT AND RETAIN CUSTOMERS BY
PROACTIVELY IDENTIFYING OPPORTUNITIES
Service in IoT can extend to sales
Sales
IoT also op>mizes support across channels and
devices, both reac>vely and proac>vely
Support
IoT enables customiza>on and
personaliza>on to help brands stay relevant
and differen>ated Customization
Collec>ng feedback and innova>ng products
and services can happen more quickly
Feedback
Innovation

16. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Manufacturing – Industry
4.0
• Sensors track products
across supply chains
• Improve Inventory
Management
• Reduce logis>cal costs and
capital expenditure

17. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Reactive
Maintenance
• Machine fails,
then fix it
Preventive
Maintenance
• Based on time or
counter schedules
Condition-
based
Maintenance
• Based on
monitoring to
assess condition
Predictive
Maintenance
• Based on models
of the evolution of
the conditions of
assets
Maintenance
Managing costs improving reliability and safety

18. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
World-wide leading manufacturer of valves,
automa-on components and other products
for high-tech process industry
Challenges
• Increase life>me and reliability of components
used in safety and health-cri>cal chemical processes
Solu-on Components
• Real->me filtering and processing of events from
equipment deployed worldwide
• Integra>on with CRM and service >cket system
Benefit
• Proac>ve and >mely parts replacement avoids
produc>on down>me
• Increased knowledge of product usage improves
product quality and func>onality
1

19. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
• Airbus SAS is a division of Airbus
Group SE that manufactures civil
aircran. It is based in Blagnac,
France, a suburb of Toulouse, with
produc>on and manufacturing
facili>es mainly in France, Germany,
Spain and the United Kingdom.
• Strong demand & compe>>on from
new players (Canada, Brazil &
China)
• Need to deliver aircran backlog
faster (~1000 new aircrans)
• Need to increase innova>ve flight
test but with less >me to perform it
• Use case
– New system need to be opera>onal
and demonstrate performance to
complete the tests of A320 Neo
whose commercial delivery is
scheduled to begin in 2015.
– Increase scalability of data storage
– Deliver higher concurrency analy>c
data access
– Scale data loading independently
from analysis
• Benefits
– Improved MTBF
– Reduce service costs
– Develop new service revenue
channels
Airbus op>mizing its manufacturing opera>ons via
Big Data on test sensors
Processing /
manufacturing
Product quality

20. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
• Responsive Machines that
always provide the most
profitable product
• Considering food varia>ons,
fluctuate pricing according to
demand
• Environmental situa>on
awareness
• Use case
– Usage, status data processed locally
and intelligently
– Real >me demand forecast for
Vending / Fountain based on
seasonality and promo>onal events
processed immediately by corporate
data centers
– Responsive and predic>ve
maintenance provided based on
individual machine requirements
• Benefits
– Efficient replenishment based on
individual use
– Immediate recogni>on of machine
failure
– Reduc>on of MTBF
Client op>mizing usage, forecas>ng and maintenance on
automated Vending Machines
Logis>cs /
Distribu>on
Channel automa-on

21. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Agenda
§ Context
§ Architecture
§ Use-Cases
§ Demo
2

22. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
How do I collect data from intelligent devices?
Abstract complexity associated with device connec-vity
Standardize integra-on of devices with enterprise
Building an IoT applica>on: Key Challenges
How do I analyze IoT Data?
Reduce noise and detect business events at real--me
Enable historical big-data analysis
How do I integrate IoT data & events with enterprise infrastructure?
Make enterprise processes IoT friendly
Allow enterprise & mobile applica-ons to control devices

23. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Internet of Things Cloud Service
Business Applica>ons IoT Devices
Manufacturing, Supply Chain, Asset Mgmt
Customer Rela>onship Mgmt, Sales, Service
Ver>cal Apps – U>li>es, Healthcare, Retail
IoT Service
Connect Analyze Integrate/Act

24. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
CONNECT
CONNECT
VIRTUALIZE COMMUNICATE
SECURE
Quickly collect data from devices
Accelerate applica>on
development
Deliver high-speed messaging
Scale to millions of end-points
Build trusted exchange
Protect end-to-end data flow

25. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
ANALYZE
ANALYZE
ANALYZE AT
REAL TIME ENRICH
STORE
Turn data into ac>onable insight
Enable edge intelligence
Add Geo data for fast ROI
Enable contextualized search
Enable BI and Big Data Analysis

26. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
INTEGRATE
INTEGRATE
INTEGRATE WITH
CONNECTORS
INTEGRATE WITH
REST APIs
CONTROL
Quickly enrich processes and apps
with IoT data
Enable rich analy>cs
Integrate with any on-prem or SaaS
applica>ons
Supports Oracle & 3rd party apps
Enable enterprise to control devices
Mobile enabled and policy driven

27. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Data Discovery & Analysis
71◦
~183kg
527
kg/m
40
Knots
Wind Speed
Sail Tension
Mast Strain
Hull Stability
Real Time
Feedback
IoT
Cloud
BigData/ Database
Engineered Systems
Gateway
Mast
Strain
Hydrofoil
Posi>on
Sail
Tension
Wind
Speed & Direc>on
Java
Devices Sensors
Wing
Posi>on
Hull Stability
Boat
Speed
Changes to boat/sailing parameters
based on Analy>cs
Challenging in real->me data processing & discovery

28. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal Oracle Confiden>al – Internal/Restricted/Highly Restricted
28
300 IoT sensors all over the boat
3,000 variables about 10 times a second
Video feeds images of the sails every second.
Live metering on the strain, mast, hull, wing
Monitor load generated from the jib to the
winches
Constantly adjust the sail wing to wind
conditions
Tablets display real-time data and predict what
will happen in the next few seconds
“The fact that we can have live
data instantaneously is key”
-- Jimmy Spithill,
Skipper, ORACLE TEAM USA

29. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Discover & Analysis on stored Data
?
Payment
Geo-Location
• Discover Insights
• Automated batch Analy>cs and Report
• Machine Learning using different datasets and sources
Passport
Classification
Associate
Report
Analyze
Compare
Discover

30. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Stream Analy>cs – Why does it mager?
?
Time Windows
Slide
Correlate Streams and Sta>c Reference
(Database, BigData, Cache, Iden>ty Directory
Aggregate and pagern recognize heterogeneous
source among different connec>on types
Geo-Fence and filtering events using manually
defined and standard maps
Machine Learning on real->me data using pre-
trained model on historical data (PMML)
Enterprise infrastructure
based on J2EE & Spark
Streaming
Func>onal responsive web
based interface
Real-Time analysis with pre-implemented common
sta>s>cal and logical func>ons

31. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal 31
Oracle IoT Cloud Service
Feature Summary
GeoProcessing
Streaming Pagerns Library
Streaming Machine Learning
Streaming Business Rules
Topology Viewer
Predic-ve
Analy-cs
Oracle Stream Analy>cs
Data Warehouse

32. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Machine Learning Analy>cs on Streaming Data
• Use of machine learning algorithms to detect pagerns & perform predic>ons based on
models created from historical data
• Streaming machine learning capable of handling very high-throughput streams,
involve two main stages:
– Model building (training)
• Uses historical data as input – may involve handling very large datasets
• Performed with low frequency
– Model scoring
• Performed with high frequency
• No historical data required - model representa>on contains all required informa>on
Predic-on stream
Machine Learning
Predic-on System
Historical data –
used to build model
Streaming data -
predic>ons performed on it

33. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Anomaly detection using K-Means
• Anomalies are events that differ or are
much less common than the majority
• K-Means is used in anomaly detection by
identifying low density clusters
– Clusters with very few members, which equates
to being less common than the majority
• A common practice is to choose the
smallest cluster as an anomaly cluster,
assuming it has significantly less
members than other clusters

34. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
BigData
ERP MES
Grande Roberta
Real-Time
• Are there pagerns of events that cause the
equipment to fail?
• What are the top factors / influencers that affect
product yield?
• What’s the downstream impact of yield change or
defec>ve parts?
• Is there a correla>on between
machine parameters and product
quan>ty?
• Can we predict the likelihood of
certain product defects?
• Are there assets used improperly or
in cau>on areas
Asset Analy>cs : Components View

35. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Grande Roberta
Real-Time
• Is there a correla>on between
machine parameters and product
quan>ty?
{
"PLANT": "A23",
"MACHINE": 34,
"PMIN": 110,
"ODEV": 0.7,
"TEMP": 38,
"PRES": 3.4,
"STATUS": "PAUSE",
"LAT": 14.453,
"LON": 42.673
}
120 msg/sec telemetry events X 6
machine sent 7 parameters, one of
those is covariance params
indicator
Real-Time clustering
events through
covariance and quan>ty
discovering low-density
cluster target
Merge Real-Time & ERP Data
Asset Analy>cs : Demo Flow

36. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. Oracle Confiden>al – Internal
Agenda
§ Context
§ Architecture
§ Use-Cases
§ Demo
3