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Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1
Roland HänggiSenior Electronics Architect, IBM Global Electronics IndustryEuropean CTO IBM Electronics Industry
The future of the IoT will be cognitive –Implications for the Smart Home
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 33
This is a experience !Die letzten >35 Jahre haben wir Technologie entwickelt und unser möglichstes getan diese als Innovation zu verkaufe.
Die Heutige jungen benutz Z.B. ihr Mobiel Phone einfach ohne über die Technik nachzudenken. Sie kaufen es weil es Cool ist oder sie optisch anspricht aber nicht wegen den Technischen Spezifikationen.
Davon sind wir alle betroffen, benutzen und nicht nachdenken wie geht dies !
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 44
Contextual intelligence is a precondition for the Smart Home vision
Contextual intelligenceMaking appliances understand what a person or other appliances in the household are doing for making the user aware of the overall environment or smooth the working process across various devices. An intelligent / smart appliance thus is understanding related events that serve a specific consumer purpose and are part of a user behavior that is analyzed for predictive activities and preventing dangerous situations.
Relevance to home appliances:§ Disabling gas if no adult is around§ Raise an alarm if a pan/cook pot is positioned
unsafe
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 55
The Internet of Things roadmap for Smart Homes
Source: Parks Associates Webcast – Internet of Things: Smart Home Success through Bundled Services
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 66
By 2020, there will be 80 billion connected devices worldwide.
Worldwide: 10 connected devices for every household by 2020
Worldwide: 5 connected devices for every user by 2020
5 billion Internet users by 2020
Approx. 500 devices with unique digital identities per square km by 2020 for the Internet of Things
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 77
The entertainment room & the kitchen are perceived as most exciting smart home areas in the house
Source: Icontrol 2015 State of the Smart Home Report
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 88
8
Connected Appliance
CA-informed customer service
Messaging Platform
Accelerate detection of production & quality issues
Diagnostics & repair Analytics
Increase first call complete %
Production Analytics
Avert unnecessary part replacement
Partner Consumables
Warranty Extensions
Replacement Appliances
Customer Analytics
•eComm Platform (partner vendor capable)
•Campaign execution & management
•Next Best Action•Price optimization•Etc.
Customer Interface Understand End Customers
Call Center Solution
Design based on extensive use data
Use & Design Analytics
Sales to CA owners
Portals
Connected Appliances includes the use cases
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 99
Example: Evaluate capabilities of robots to interact with humans Robot as sales staff at an appliance store
(1)Findcustomers
(2)Approach
(3)Estimatethecustomer
(4)Assemblesalesplans
(5)Leadconversation
(6)ProductQ&Aanddemo
(7)Confirminventory&delivery
Full-text recognition
People perception
POMDP settings
Proactive Q&A
Goal-oriented task flow
Customer recognition
External devices
People tracking
Age and gender estimation
Word-level recognition
Computervision
Speechtechnology
ComputervisionSensingControlActuatorsDynamics Computervision
MachinelearningSpeak Speechsynthesis
Characterdesign
Gestures MotionCharacterdesign
Reactive Q&A
Autonomic level flow
External systemse.g.,CRM
e.g.,remotecontroller
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1010
IoT in Insurance: The Connected Insurer
Today, we see 3 main areas where the insurers are focused1. Connected Home for risk mitigation2. Connected Car for driving behavior and services 3. Connected Life for health and wellness and disease
management
Connected Home
Connected Life
Connected Car
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1111
How to make a Smarter Home intelligent
• Assuming to have in 2020 80 billon of connected devices, the difference how to improve them. (Structured Data)
• Sensor Data only is not enough we need to correlate them with globally available information.
• Global available data are mainly unstructured.• Also Humans nowadays like to communicate with with technology in
natural language.• To process natural language and unstructured data cognitive
computing is needed.
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1212
Cognitive systems are fundamentally different from what we have today
Adapt and make sense of all data; “read” text, “see” images and “hear” natural speech with context
Understand
Reason Interpret information, organize it and offer explanations of what it means, with rationale for the conclusions
Learn Accumulate data and derive insight at every interaction, perpetually
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1313
Complexity of IoT solutions IoT is a monumental programming challenge
Programmable computing thrives in prescribed, predictable scenarios but is too limited for the complex IoT landscape.
Cognitive systems aren’t programmed. They learn from virtually every interaction and the surrounding context to unleash the potential of the IoT.
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1414
Cognitive computing can relieve the cognitive overload from data volume & complexity
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1515
Advanced analytics integration in IoT apps
Textual Analytics
Natural Language Processing
Video / Image Analytics
Machine Learning
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1616
Watson Cognitive Services: APIs available
Language • AlchemyLanguage• Concept Expansion• Concept Insights• Conversation• Document Conversion • Language Translation• Natural Language Classifier • Personality Insights• Relationship Extraction • Retrieve and Rank • Tone Analyzed
Speech• Speech to text • Text to speech
Vision • AlchemyVision• Visual Insights• Visual Recognition
Data Insights• AlchemyData News• Tradeoff Analytics
http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/services-catalog.html
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1717
Question as a string“Will the storm hit job site #123 tomorrow ?”
Question’s class (e.g. temp, rain, snow, wind etc.)Class=‘weather’Class=‘snow’
WAV files
WAV files
(Class, Location, Time)(‘Tomorrow’)
Weather data for specified time and locationChances of stormy weather in Detroit tomorrow is 20%‘ Stores DB
Job site #123 is in Detroit MI
Mixing cognitive and “standard” analytics for a solution with well-defined scope
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1818
“ForValentinesDay,IwanttotakemywifetoParis.CanyoubookaHiltonHotelforme?”
Cognitive Enables Human-centric Analytics
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 1919
Cognitive Enables Human-centric Analytics
Web Search Engine
“ForValentinesDay,IwanttotakemywifetoParis.CanyoubookaHiltonHotelforme?”
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2020
Cognitive Enables Human-centric Analytics
Web Search Engine Siri
“Calling Mr. Valentine”
“ForValentinesDay,IwanttotakemywifetoParis.CanyoubookaHiltonHotelforme?”
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2121
Cognitive Enables Human-centric Analytics
Web Search Engine Siri
“Calling Mr. Valentine”
“ForValentinesDay,IwanttotakemywifetoParis.CanyoubookaHiltonHotelforme?”
Cognitive Interaction
§ Do you also need flight bookings to Paris?
§ Do you need flowers in the room?
§ Do you want a dinner reservation?
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2222
Celebration
Couples
Flowers
Trip
Dinner
RomanticFeb 14
…
“Watson 101” –how It Works –Building Semantic Networks
“ForValentines Day,IwanttotakemywifetoParis.CanyoubookaHiltonHotelforme?”
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2323
Celebration
Couples
Flowers
Trip
Dinner
RomanticFeb 14
…
“Watson 101” –how It Works –Building Semantic Networks
“ForValentines Day,IwanttotakemywifetoParis.CanyoubookaHiltonHotelforme?”
From
To
Plane
Train
Car
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2424
Celebration
Couples
Flowers
Trip
Dinner
RomanticFeb 14
…
“Watson 101” –how It Works –Building Semantic Networks
“ForValentines Day,IwanttotakemywifetoParis.CanyoubookaHiltonHotelforme?”
From
To
Plane
Train
Car
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2525
Celebration
Couples
Flowers
Trip
Dinner
RomanticFeb 14
Trip
DestinationPlane
Car
Hotel
Schedule
City
Europe
Destination
Romantic
Family
Hotel
Celebrity
ParisLondon
…………
“Watson 101” –how It Works –Building Semantic Networks
“ForValentines Day,Iwanttotake mywifetoParis.CanyoubookaHilton Hotelforme?”
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2626
Celebration
Couples
Flowers
Trip
Dinner
RomanticFeb 14
Trip
DestinationPlane
Car
Hotel
Schedule
City
Europe
Destination
Romantic
Family
Hotel
Celebrity
ParisLondon
…………
“Watson 101” –how It Works –Building Semantic Networks
“ForValentines Day,Iwanttotake mywifetoParis.Canyoubooka HiltonHotelforme?”
In reality, Watson is a bit more complicated than this:• Connections have „weights“ to them – if the answer is identified as correct during a learing
phase, links become stronger; if it is wrong, links become weaker• Same applies to the semantic network itself. As Watson‘s knowledge base grows, semantic
networks become broader and deeper• Today Watson has semantic networks that have thousands, sometimes millions of terms to
them
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2727
Typical Home appliance today or near future
All this home appliance are connected and programmable but not cognitive. They only understand structured sentence and not natural Language
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2828
Some example to illustrate the difference
• Asking a question about the weather with those devices looks like– What's the weather outside/Baden?– What’s the Weather here and in Munich on Wednesday till
Friday?– Please book me a hotel room in Munich?
• Using natural language you could ask– Do I need to carry an umbrella when I travel to Baden?– I’m traveling to Munich on Wednesday how should I dress me u– up?
• Do you have already a flight booked?• Do you need a hotel room? • …
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 2929
Some more cognitive use case for a smarter home
• Assuming all this device has an camera, speaker and microphone they could act as watch dogs.– With personalized profiles of each person in the house hold
recognizing the voice picture and personal preference and habits.
– Somebody enters the room camera uses face recognition service to recognize who it is of if the person are not living at this home.
– Somebody enters the home and says something microphone uses voice recognition service to recognize who it is of if the person are not living at this home.
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 3030
Some more cognitive use case for a smarter home (cont.)
• Assuming all this device are fully connected and person comes home after stressful day.– With personalized profiles of each person in the house hold
recognizing the voice picture and personal preference and habits.
– Person says with angry voice “I had a horrible day, I need a cool beer”
– Voice mood analysis recognizes stress, tone analyzer recognizes stress based on the wording in the sentence.
– Adjusting the response voice with an more assuasive voice and response based on the profile information.
–
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 3131
In the dress room
• How shall I dress me up today– Weather information, casual, business, weekend – Keyword area
• Location• Day of the week• Profile information
• I’m going on vacation to Dubai next Sunday for 10 days.– Weather information what is needed because of temperature ,
season related, vacation as dress indicator,– Keywords are
• Vacation• Location Dubai• Weather at location• Next Sunday (exact date)• Duration• Profile information
Smart Home 2017 | Roland Hänggi | 21.03.2017 | © Electrosuisse 3232
In the bad room
• What's the weather forecast for today– Keyword area
• Location• time
• I want to book a restaurant – Keyword area
• Location• Restaurant using profile information
• Please order me a taxi for– Keyword area
• Location• Normal taxi, UBER using Profile info.