The Internet of Things, Ambient Intelligence and the Move Towards Intelligent Systems
Santa Clara (IEEE Region 6) EventSeptember [28 or 29], 2012
Dr. George Vaněček, Jr.Senior Principal Scientist, FutureWei Technologies, Inc.
Our Next 40 Minutes…
1. From Internet to Internet of Things (IoT)and Beyond
2. Growing Intelligence in the IoT3. Something about Sensing, Real-world
Perception, and Context-Awareness4. The Tools of the trade5. Key Takeaways6. Key Technologies
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It has been a great ride
Let’s celebrate the Internet and the Web, and everyone who had some small part in them, on changing the world for the better!
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http://ww
w.unc.edu/~unclng/Internet_H
istory.htm
Now get ready for a far stranger ride, we never imagined only a few decades ago.
Looking ahead to Future Internet/Web, more Challenges remain…
Ubiquitous personalization and individualization– Global Identity, Trust, Presence, Ownership, …
Portability between Silos– Of Identities, Profiles, and Content
Information OverloadAbility to scale beyond human-only usage– More addresses, storage/transport capacity, devices, …
Machines Understanding of Data– Unstructured, Semi-structured and Structured data
Interoperability with– Open Data, Formats, and APIs
Context/Situation/Intent AwarenessDigital-world is becoming aware of the
physical-world: Internet of all things
Here comes the Internet of ThingsThe Internet will connect billions of people through mobile and embedded smart devices.Real-time communication and the accessibility to any information on-line will enrich people and machines; …the Internet will connect everyday things integrated into people’s every day lives.– More equipment will be connected to the Internet than
people by a factor of 8 to 1 (50 Billion by 2020).IoT will integrate many industry verticals(e.g., healthcare, energy, transportations) into smart*/city/building/home environments.IoT will be centric to people’s needs and every day existence.
Ambient Intelligence will expand.
IoT will bring us theSmart Connected World
Smart Homes
Smart Buildings
Smart Cars
Smart Phones
Smart City
Smart Grid
Smart Community
Smart Highways
The rise of Ambient Intelligence: The Personalization, Socialization, and Real-world Awareness of the Internet
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Today
ManyMany(Personal)(Personal) Computers for Computers for OneOne Person Person
Size
Number
Computer
One Computer for Many People
Tomorrow
ManyMany(Hidden) (Hidden) ComputersComputersfor for ManyManyPeoplePeopleOne Computer
per One Person
So, What is Ambient Intelligence?
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AmI refers to electronic environments that are sensitive and responsive to the presence of people
“In an Ambient Intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in easy, natural way using information and intelligence that is hidden in the network connecting these devices.” Source: Wikipedia
Source: Wikipedia
The Challenge for the Industry
Create an infrastructure and middleware to•enable heterogeneous devices to interoperate,•to perform assigned tasks, and•be able to sense, perceive and react appropriately•with minimal human intervention (Organic Computing).
From Existing to Intelligent (Organic Computing) SystemsNeed intelligence in systems thatdynamically adapt to their environment and
tasks, and areSelf-Configuring,Self-Describing/Explaining,Self-Healing,Self-Protecting,Self-Organizing,Context-aware, andReactive and Proactive.
2012: 1.2 Zetabytes (1.2 x 1021)Will grow 44 fold in the next Decade
Understanding Data is the Starting Problem
Digital World: Deluge of Data– Structured (some)– Semi-structured (a bit more)– Unstructured (huge amounts of)
Audio, Video, text, PPT, Doc, … Physical World: Deluge of Sensor Data– Mostly Unstructured
Source: IDC
Increasing Intelligence in Systems
“Intelligent Systems will exist in environments they sense and perceive, and from which they learn and continually act to achieve their objectives.”
1. sense the real-world environments,2. perceive the world using world
models,3. adapt to different environments
and changes,4. learn and build knowledge, and5. act to control their environments.
They are computational systems that behave intelligently and rationally, to
AmI Pipeline to WisdomUn
ders
tand
ing
Ability to Act
Information
UnderstandRelationships
Knowledge
UnderstandPatterns
Wisdom
UnderstandPrinciples
Going from “What happened” to “What will happen”
SensePervasive sensing of
the Environment
PerceiveAbility to
infer reln’s from data
ActTake an
action on behalf of
the humans
LearnLearn form patterns
and events
AdaptAdapt
based on needs
Data
Actuators andOn-Line Services
AnticipateReact
Execute
Unstructured, Semi-Struct., andStruct’ed On-line and Sensor Data
Modern AI Explosion
1950 1980 1990 2010
AI P
rom
ises
and
Exp
ecta
tions
1970
Decision TreesFinite State MachinesSymbolic ReasoningLogic Programming
General Problem SolverLisp Programming Language
Fraud DetectionSpam Filters
Search EnginesNatural Language Processing
Biometric, face/fingerprint detectionRobotic and Machine Translation
Speech UnderstandingBusiness IntelligenceCollective Intelligence
Data MiningAutonomous Systems
Machine LearningPredictive AnalysisPattern Matching
Sensing, PerceptionReal-world ModelingBehavior Modeling
…
Prolog Declarative LanguageNeural Networks
Knowledge RepresentationsCommercial Expert Systems
Before 1990, classic AI goals were to surpass human intelligence in
Language,Reasoning, &Abstract Problem Solving
Big Data and Data Science Challenges
The challenges that are being solving for are:– How to handle large data volumes?– What data to store?– How to analyze it?– How to find significant data?– How to use it to best advantage?– How to visualize the data?– When to analyze the data and when to apply its results?
Big data focuses primarily on statistically finding patterns, trends, risks, and meaning in large amounts of collected (unstructured) data from access logs, transactions, tweets,
emails, blogs, etc.
MapReduceHadoopMongoDB
Machine Learning
Supervised Learning Algorithms– K-Nearest Neighbor– Naïve Bayes– Support Vector Machines– Decision Tree Induction– Etc.
Unsupervised Learning Alg.s– K-Means– Expectation Maximization– Etc.16
ML refers to a statistical suite of algorithms and paradigms for finding patterns in data.
Training Set {x}
Training Algorithm:
X’D
{[Patterni,Di]}
{D}
{}
Machine Learning and AI Join Forces
Build systems that learn about self and environmentCreate Situated Autonomous Decision Systems– in dynamic environments over extended time
entrusted to handle complex tasksTeach autonomous systems how to handle time, change, and event streams.
Most systems do not handle time and changes wellBuild Agents that exhibit life-long Machine Learning (ML) rather than ML algorithms that learn one thing only.Create an interchangeable world knowledge for Intelligent Systems. Source: AAAI-96
From “What happened” to “What will happen”
AmI Requires ways to Model and Represent the Worlds
with the understanding of– Global Identities of people, places and
things,– Multiple contexts,– Situations,– Intents,– Trust based on evidence, and– Behaviors and Habits,
Time and Histories.18
Taxonomies: explicit hierarchical specifications of related categories/entities and rules to differentiate themDomain-Specific Ontologies: descriptions of entities and their relationships
AmI Means for Building Models of the Real-World
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Knowledge Bases: Graph-based entity-relational knowledge repositories
Software Agents: Autonomous programs sensing and performing various duties.
Engines that can analyze, reason, plan, predict
Semantic Web…
Semantic Web, the Web of Data andthe Meaning of Data
When the web can understand content, it will then better satisfy people and machines
requests
A Web where the context of content is defined by dataA Web capable of reading and understanding content and context
Tim Berners-Lee
Around 2006, the Semantic Web emerged as an evolution to Web 2.0 to be
Refocusing on Context-AwarenessRefocusing on Context-Awareness
Microformatsdata embedded within XHTML
Metadatastatements about the
world in a manner that machines can understand
unambiguously
When authors create content, they will need to define the context that links the content to their target audience
Cross-linked and DefinedData Models
Resource Description FrameworkDefines and describes data andRelations among them
ContentTags
When machines generate content, they will also need to define the context
OntologiesOWLWeb Ontology Language
“The Internet is a Changing”Key Takeaways– The digital world is becoming more aware of
the real world– Systems are becoming more intelligent and
autonomous– Everyday things are getting connected– Technology and computing is becoming
transparent– Rapid innovation is driving major changes in
the IoT– Ambient Intelligence and Organic Computing
is gaining Industry focus22
Key Technologies to FollowSemantic Web– Meta Data– Ontologies and
TaxonomiesHTML5 and D3jsRTW and WebSocketsData Fusion– Processing
unstructured/semi-structured Data
Machine Learning
Information/Knowledge Repositories– NoSQL Databases– Graph Databases– Knowledge Bases
Dynamic and Post-Functional Languages– Scala, Python,
Java 8, Groovy, Haskell, Lisp, Javascript, …
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Thank [email protected] Clara, CA