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Definitions and Application Areas Ambient intelligence: technology and design Fulvio Corno Politecnico di Torino, 2013/2014 http://praxis.cs.usyd.edu.au/~peterris

Ambient Intelligence: Definitions and Application Areas

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Topics: - Definition(s) - Application areas - Requested features - Architectures Slides for the course of "Ambient Intelligence: Technology and Design" given at Politecnico di Torino during year 2013/2014. Course website: http://bit.ly/polito-ami

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Page 1: Ambient Intelligence: Definitions and Application Areas

Definitions and Application Areas Ambient intelligence: technology and design

Fulvio Corno

Politecnico di Torino, 2013/2014

http://praxis.cs.usyd.edu.au/~peterris

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Summary

• Definition(s)

• Application areas

• Requested features

• Architectures

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DEFINITION(S) Definitions and Application Areas

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What is Ambient Intelligence?

• Wide area

• Expectations evolving over time

• “Definition” or “prediction”?

• Multiple definitions found, from complementary points of view

• Some researchers trying to define a common framework

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The starting point

• The concept of Ambient Intelligence (AmI) provides a vision of the Information Society where the emphasis is on greater user-friendliness, more efficient services support, user-empowerment, and support for human interactions. People are surrounded by intelligent intuitive interfaces that are embedded in all kinds of objects and an environment that is capable of recognising and responding to the presence of different individuals in a seamless, unobtrusive and often invisible way.

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Some other definitions

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Comprehensive AmI definition

• “An Ambient Intelligence system is a digital environment that proactively, but sensibly, supports people in their daily lives”

Cook et al, Ambient Intelligence: Technologies, applications and opportunities, 2009

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Comprehensive IE definition

• “An Intelligent Environment is one in which the actions of numerous networked controllers (controlling different aspects of an environment) is orchestrated by self-programming pre-emptive processes (e.g., intelligent software agents) in such a way to create an interactive holistic functionality that enhances occupants experiences.”

Augusto et al, Intelligent Environments: a Manifesto, 2013

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Interactions among disciplines

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Main steps for AmI

Sensing

Reasoning

Acting

Interacting

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Sensing

• Sensors, sensor networks

– Wired or wireless

– Independent or embedded in a device (eg. Smartphone)

• Ambient or body

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Examples (ambient, wireless)

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Examples (wearable)

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http://www.notchdevice.com/ Inside clothes Haptic Feedback Movement capture

Metria™ Informed Health 3-axis accelerometer, Galvanic Skin Response, 2 temperature sensors (body, skin)

Self-tracking Steps, calories, sleep, distance, …

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Sensor data

Huge Noisy

Missing points Heterogeneous

measures

Time- & space- dependent

Raw vs. processed

• “Making sense of data”

• Stream data processing

• Signal processing algorithms

• Sensor fusion

• Big data handling

• Filtering, disambiguation, interpretation

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Reasoning

• Needed to provide responsiveness and adaptability

• Interpret and recognize context and activity

• User modeling, context modeling

• Context detection and context awareness

• Mobility tracking

• Activity recognition, activity prediction

• Decision making

– Acting vs. suggesting

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Acting

• Home automation systems (lights, doors, windows, temperature, …)

• User Interfaces or Wearable devices (notifications, information, alerting, …)

• Robots

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Interacting with users

• Traditional user interfaces

– Web, mobile

• Home fixtures

• Natural user interfaces

– Speech, gestures, body motion tracking, emotions, facial expressions, attention, …

– Interaction bypasses ICT equipment (“disappearing computer”)

• Should be the most important aspect of an AmI, but…

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Related Buzzwords…

• IoT – Internet of Things – Physical objects are part of the Internet infrastructure.

Objects are capable of interacting with other objects

• M2M – Machine to machine communication – Technologies that allow both wireless and wired systems to

communicate with other devices of the same type

• IoE – Internet of Everything – The Internet of Everything is the networked connection of

people, process, data, and things (Cisco)

• Smart Homes, Domotics – Today’s solutions, with limited or no intelligence

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APPLICATION AREAS Definitions and Application Areas

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Application areas

• The general principles are applicable to different types of environments

– Private homes

– Public/shared buildings

– Open spaces

• The type of applications is extremely varied

• The approach and many founding technologies are shared across application domains

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Some application areas

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Note: Just “Smart” or

Really “Intelligent” ?

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A recent example…

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https://nest.com/

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REQUESTED FEATURES Definitions and Application Areas

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Features

• What are the features characterizing an AmI system?

• What is really an “intelligent” system, versus a “smart” one, versus an “automated” one?

• What characteristics are implied by the AmI definition(s)?

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Features

AmI

Sensitive

Responsive

Adaptive

Transparent

Ubiquitous

Intelligent

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Sensitive & Responsive

• Able to sense

– The environment

– The occupants

• Able to process sensor data

• Able to respond to user needs

• Able to act on the environment

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Adaptive

• Able to infer a situational context

– From environment data

– From user data (identity, presence, actions, …)

– From statistics and preferences

– From external information sources

• Able to adapt to the context

– the interpretation of sensing

– the generated response

• «Context-Aware Computing»

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Transparent

• «The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it» (Weiser, 1991)

• «Disappearing computer»

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Ubiquitous

• Ubiquitous Computing, Pervasive Computing

– Ubiquitous: present, appearing, found everywhere

– Pervasive: spreading widely throughout an area or a group of people

• Able to be distributed over the ambient and over different people

• Requires mobility, miniaturization, wireless communications, energy management

• Requires interoperability, discovery, self-configuration

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Intelligent

• Incorporates Artificial Intelligence:

– Machine learning, agent-based software, robotics

– Hearing, vision, language, knowledge processing

– Semantic web, reasoning

• AI is an enabler for achieving context awareness, adaptivity, proactive responsiveness

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ARCHITECTURES Definitions and Application Areas

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AmI requires complex systems

• Drawing from may different fields of Computer Science and Electronics

• Requiring the most advanced solutions for integrating such diverse and numerous subsystems and devices

• Needing to switch from one-off prototypes to scalable, reusable, plug&play, industrially robust solutions

• Industries and researchers need to play together with standardization initiatives

• Need to (re)gain the central role of end users

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Home automation technologies

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Home automation technologies

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RS-485

Home Automation

Building Automation

Informatica

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Standards?

• Users are in the hands of manufacturers

• Technologies and protocols

– Don’t interoperate

– Rapid obsolescence

– Don’t trust new «Universal Standards»

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http://xkcd.com/927/

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System overview

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D D D D

Application

Devices

• Tecnologie dei sensori • Protocolli di comunicazione • Scala (locale, geografica) • Numero di dispositivi • Frequenze di

campionamento • Sicurezza / autenticazione • Tipologia dei dati • Unidirezionale o

bidirezionale • Codifica dei dati • Polling / Pushing

Infrastructure & AmI

• Sensori ambientali (temperatura, umidità, CO2, inquinanti, illuminazione, vento, …)

• Sensori utente (presenza, movimento, accessi, …)

• Misuratori energetici (energia e potenza elettriche, consumi gas e acqua, …)

• Attuatori (relais, elettrovalvole, motorizzazioni, segnalatori, …)

• Sistemi di automazione • Tipologie di interconnessione

• Cruscotti (osservazione, monitoraggio, …) • Dati storici (memorizzazione,

consolidamento, consultazione, …) • Allarmi (anomalie, superamento soglie, …) • Controllo remoto (comando attuatori,

dis/attivazione azioni, modifica set-point, …) • Tendenze (analisi su dati storici, analisi su dati

in tempo reale) • Elaborazioni in tempo reale (calcolo

grandezze derivate, sensori virtuali, …) • Intelligenza ambientale (comfort, risparmio

energetico, applicazione scenari, adattamento dinamico, …)

• Integrazione con sistemi informativi

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In the real world

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D D D D

Devices

AmI Infrastructure

Application

Application

Application

Application

Application

D Wired

Wireless

Custom-made

Appliance

Internet

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Errors to avoid

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D D D D

Application

Devices

Infrastructure

D D

D

D

Application

Infrastructure

D

«All you can eat» application The «tooooo smart gateway»

Devices

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Target approach

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AmI system

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Open Horizontal AmI Architectures

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D D D D D D D D D D D D

Application Application Application Application

Neutral representation

Basic services

API

Protocol interfaces/drivers

Data exchange

Real time processing Intelligence Application (service, agent)

Intelligence

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An example middleware

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D D D D D D D D Domotic devices (switches, buttons, relays, sensors, meters, …)

Domotic bus (wired, wireless)

GW Bus-to-IP gateway Bus-to-serial gateway GW

Ethernet, Wi-Fi, USB

User Interface

Mobile, Web, Home Display, Multi Touch, Accessibility, Natural language, …

Data analysis

ERP, Web services, Stream processors, Datawarehouse

Dog Bundles

Device abstraction, Event abstraction, State abstraction, Rules engine, …

User Interface

User Interface

Smart Appliance

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Resources

• Scenarios for Ambient Intelligent in 2010, ISTAG Group, 2001 • Smart Environments: Technology, Protocols and Applications,

DJ Cook, S Das, John Wiley & Sons, 2004 • How smart are our environments? An updated look at the

state of the art, DJ Cook, SK Das - Pervasive and mobile computing, 2007

• Ambient intelligence: Technologies, applications, and opportunities, DJ Cook, JC Augusto, VR Jakkula - Pervasive and Mobile Computing, 2009

• Intelligent environments: a manifesto, JC Augusto, V Callaghan, D Cook, A Kameas, I Satoh - Human-centric Computing and Information Sciences, 2013

• Ambient Intelligence: A Survey, F Sadri, ACM Comput. Surv., October 2011

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License

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• These slides are distributed under a Creative Commons license “Attribution – NonCommercial – ShareAlike (CC BY-NC-SA) 3.0”

• You are free to: – Share — copy and redistribute the material in any medium or format – Adapt — remix, transform, and build upon the material – The licensor cannot revoke these freedoms as long as you follow the license

terms.

• Under the following terms: – Attribution — You must give appropriate credit, provide a link to the license,

and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

– NonCommercial — You may not use the material for commercial purposes. – ShareAlike — If you remix, transform, or build upon the material, you must

distribute your contributions under the same license as the original. – No additional restrictions — You may not apply legal terms or technological

measures that legally restrict others from doing anything the license permits.

• http://creativecommons.org/licenses/by-nc-sa/3.0/