Joint Presentation Panasonic and IBM at TU-Automotive Japan 2016 ( http://www.tu-auto.com/japan/ ): - Understand how machine learning across multiple industry domains creates a new mobility experience - Explore a coherent framework combining embedded, edge and cloud-computing elements to better predict vehicle and driver needs

1. Managed Business Process ServicesReveal the Car’s Potential with Cognitive IoT
Yuri Tsuji
Manager, Product Planning Silicon Valley Center, Panasonic Automotive Systems Company of America
Dr. Sebastian Wedeniwski
IBM Distinguished Engineer, CTO Automotive/Aerospace & Defense/Industrial Products Global Industry

2. IN
PANASONIC CROSS VALUE SOLUTIONS
Smart Homes.. Smart Cities…
Better Life… Better World…
Components to Solutions Cross Value
Innovation

3. IN
PANASONIC DOMAINS & SOLUTIONS & PRODUCTS
3
Cross Value
Innovation

4. IN
PANASONIC 4 GLOBAL DIVISIONS & SILICON VALLEY CENTER
4
Cross Value
Innovation

5. IN
PANASONIC SILICON VALLEY CENTER
5

6. IN
PANASONIC & COGNITIVE MOBILITY
6
Unlimited content integration
User Generated• Social Networks •
Ecommerce • Corporate •
Collaboration • Others…
Personalization
Preferences • Brands • Lifestyle •
Entertainment• Merchants •
Activities • Travel
Unlimited triggers
Location • Speed • Sensors •
Databases • Others…
Connectivity technologies
Personal – Local – Wide •
Area Networks,Micro Location..
Panasonic
One Connect
Content Streaming
Platform
Personalized Contextual Content
Delivery to fit user lifestyle and
needs
Avionics
IFE
Mobile
Devices
Car
IoT
Appliances
Wearables
e-Token
Smart Key

7. IN
PANASONIC ONE CONNECT – IN CAR INTELLIGENCE
7

8. IN 8
Cognitive Mobility
Connectivity Technologies
Personal – Spaces, Places, Devices
Content Streaming Platform
Personalized Contextual Content Delivery to
fit user lifestyle and needs
Unlimited Data
Locations • Events • Sensors
Vehicle APIs • Media Units
Databases • Others…
Unlimited Interactions
User Generated • Social Networks
Commerce • Campaigns • Corporate
Conversation • Collaboration • Others…
Personalization
Preferences • Brands • Lifestyle
Entertainment • Merchants • Context
Activities • Travel • Others…
Mobile
Devices
Avionics Car
IoT
Edge
Devices
PANASONIC & IBM COGNITIVE MOBILITY EXPERIENCE CAPABILITIES
A unified platform to manage “Who,”
“What,” “Where,” “When,” and “How”
Cognitive Ecosystem
Semantic Integrationof Dynamic Services
to learn customer mobility experiences

9. IN 9
PANASONIC & IBM VISION
http://think-automobility.org/convergence-collaboration-and-the-future-of-cognitive-cars

10. What is Artificial Intelligence? What is the difference between
Artificial Intelligence, Cognitive, and Machine Learning?
large amount of data
Artificial intelligence is technology that appears to emulate human performance typically by learning, coming to its own conclusions,
appearing to understand complex content, engaging in natural dialogs with people, enhancing human cognitive performance (also known as
cognitive computing) or replacing people on execution of non-routine tasks.
http://blogs.gartner.com/it-glossary/artificial-intelligence/
Cognitive systems use deep natural language processing and understanding to answer questions and provide recommendations and
direction. The system hypothesizes and formulates possible answers based on evidence, can be trained through the ingestion of vast amounts
of content (including unstructured and semi-structured information), and automatically adapts and learns from its mistakes and failures.
(IDC's Worldwide Semiannual Cognitive Systems Spending Guide Taxonomy, March 2016)
Artificial intelligence and cognitive technology use advanced machine learning and natural language processing to discover insights in
data, suggest actions, and continuously learn by mimicking natural human cognitive functions.
(The Top Emerging Technologies To Watch: 2017 To 2021)
Divides Artificial Intelligence into three types: Artificial Narrow Intelligence (expertise in a field), Artificial General Intelligence (matches
human intelligence across any field), and Artificial Super Intelligence. Machine Learning (NLP, deep learning, computer vision, data mining,
etc.) is a key type of AI technology.
natural language
processing
Cognitive System
machine
learning
insights & confidence
Cognitive Systems enable decision makers to act with confidence;
they do not make decisions that mimic human intelligence likeArtificial Intelligence

11. Example IBM Watson Conversation Service
Description
• Enables Developers with Business
users to create natural, human-
like conversational experiences
across all channels (e.g. mobile,
messaging, robots, etc.)
• Combines Intents, Entities and
Dialog into a seamless experience

12. Example IBM Watson Conversation Service
Intents and Entities for an example Coffee Service

13. Example IBM Watson Conversation Service
Dialog for an example Coffee Service – machine learning conversation flows

14. Example IBM Watson Conversation Service
Two ways to make an order: know exactly what you want or need a suggestion

15. Example IBM Watson Conversation Service in Commerce domain
Blockchain will get a critical platform in a software-defined online&offline architecture
Cognitive Mobility Cloud
Personal Profile
Vehicle and Location Based System Map Analytics
Conversation Event Management
Content
Integration
Real-time
Analysis
Cognitive Vehicle
Vehicle Electronics HMI Agent
Mic
Audio
Steering
Wheel
Head
Unit
Instrument
Panal
Heads Up
Display
Vehicle Probe
Data
Hybrid Conversation
User Data
STT TTS
Vehicle Event
Manager
Connection Manager
Connection
Management
Data
Transformation
Location Data
Processing
Location
Analysis
Data
Orchestration
Personal
Operational
Data
STT
TTS
Dialog
Manager
NLU
Personal
History
Intelligent Module
Privacy
Shared
ledger
Smart
contract
Consensus
Every piece of software is like a contract (some signed by OEM, some by driver/owner) where a
consensus with all software parties is needed in a Cognitive Vehicle. All changes are immutable
in a distributed, shared Bill of Materials across various software configuration patterns.

16. Example IBM Watson Conversation Service in Commerce domain
Integration example for the In-Vehicle Infotainment

17. But conversation is only one use case of 142 other related to a
Cognitive Vehicle

18. …further details
The Mobility Revolution in the Automotive Industry: How not to miss the digital turnpike!
The Internet of Things, Cloud Computing, Connected Vehicles, Big Data, Analytics – what does this have to do with the automotive industry? This book provides
information about the future of mobility trends resulting from digitization, connectedness, personalization and data insights. The automotive industry is on the verge of
undergoing a fundamental transformation. Large, traditional companies in particular will have to adapt, develop new business models and implement flexibility with the
aid of appropriate enterprise architectures. Transforming critical business competencies is the key concept. The vehicle of the digital future is already here –who will
shape it?
http://www.amazon.co.jp/dp/4627486316
http://www.amazon.com/dp/3662477874
http://www.amazon.com/dp/3662447827
http://www.springer.com/us/book/9783662477878
http://www.springer.com/de/book/9783662447826

19. Development Model between Panasonic Automotive and IBM AutoLab
AutoLab Offerings
(Buemix Garage)
Come in with
1/2 -1 Day 2-5 Day 4-10 Weeks 12+ Weeks
Selection of a use
case or specific
application
Scope of MVP
defined.
Hypothesis
identified.
Business/IT
alignment.
Design Workshop
defines clear MVP
scope.
Successful MVP
app built &
deployed.
Client embracing
Garage Model.
What you get
Need to scale to
multiple application
use cases (and
teams
Sustainable
application dev
teams on Bluemix
High level
innovation agenda
and/or pain points
for MVP identified
MVP Selection
Understanding of
the AutoLab
Garage Method
Start with a
disruptive idea
Experiment
and design
the app
Build on
Bluemix
Integrate with
what you
have today
Define
MVP
Scale
ConnectActivateCo-Create

20. In Summary
Today
hardware-defined
Future
software-defined
Future in partnership with
IBM & Panasonic
data-defined
How to build physically a safe and
reliable vehicle?
HMI is primarily defined by the cockpit.
Cockpit is based on multiple,
independently hardware-defined
devices in an AUTOmobile.
How to digitally integrate the driving
experience and update vehicle
services during driving?
HMI is primarily a software-defined
integration of multiple channels into one
cockpit system (e.g. Audio/NLU, Haptic
Steering, Haptic Brake, Heads Up Display,
Lights, Mirrors, Head Unit, Smartphone
App, Key/Wearable).
How to build a learning space to
personalize the vehicle and
services?
Personalized HMI is a semantic
integration of data-definedservices
related to Spaces, Places and Devices. A
dynamic ecosystem creates new business
models around the autoMOBILE.
Smartphone CompanionApp
Media client built into the head unit,
permanently available
Connectivity via built-in SIM card or
Smartphone as modem
Traditional approach
to design SW BOM & OTA
New kind of SW BOM design
OTA based on Blockchain