IoT Day 2014, TrentoTrento at the centre of the Italian Internet of Things

Connect your Things!

Don’t be an alien!

organised by @iotitaly

hashtag for this event #trentoiot

iotitaly

iCore: smart things for smart applicationsRaffaele Giaffreda, IoT Day Italy, TrentoRaffaele Giaffreda, IoT Day Italy, Trento

9th April 2014

outline

• the scale of Internet of Things

• the bottlenecks

• some research results

• some future trends• some future trends

• conclusions

some numbers

• 9.3bln people on earth by 2050 (70% urban, source WHO) –2.5bln in 1950

• increasing stress on planet resources – up to 50% world produced food goes to waste (source IMECHE –

2013)

– 30% water lost in transit (source WHO and various reports)– 30% water lost in transit (source WHO and various reports)

– substantial room for improvement

• age 65+: 516m 2009, 1.53bln by 2050 (source US Census Bureau) � healthcare issues!

• future cities have no choice but to become smart...IoT gives them the opportunity to sense problems and adjust...

• 50bln connected things by 2020?

some more numbers

• BOSCH: 7bln by 2015

• ABI research: 30bln by

2020

• Cisco: 50bln by 2020• Cisco: 50bln by 2020

• Morgan Stanley: 75bln

by 2020

wearables at CES2014

substantial demands

on communication

infrastructure

substantial demands

for resource

constrained IoT

da

ta fro

m 5

0b

ln d

ev

ices

infrastructure

substantial demands

on centralised

targeted usernetwork

some research results

pics from IoT Italy Hackathon 2013

The Dumb IoT The Craft IoT The Cognitive IoT

YESTERDAY TODAY TOMORROW

from IoT Italy 2013

Bear with us, we are building it!

An example...

• “I am hot”

• thermostat lowers temperature

• but...

• energy efficiency (target)• energy efficiency (target)

• light sensor, outdoor temperature (available)

• cognitive IoT system lowers the blinds instead

or it shuts the windows or ...

compare user intervention and

automated system based on templates

other examples

• “I am going out of the house”

– switch off lights, water plants, activate iRobot, close curtains...

• “I am unwell”• “I am unwell”

– monitor health parameters, stream data to doctor, remind me of taking medicines

• moreover “social” things can discover and

support each other based on relatedness

the basics – how do things become

smart?

• acquire and log data

• analyse it and learn patterns

• create predictive models

– anticipate user intentions in routine jobs (water – anticipate user intentions in routine jobs (water

the plants, feed the fish, switch off lights)

– produce non-expert alerts (a leak, a fire, a fault in

a car etc.)

how is that achieved?

iCore Real World and System

Knowledge models

Real World Knowledge

(RWK)

Models

derive patterns of ...

interpret

data

data goldmine

System Knowledge

(SK)

Models

presence

derive patterns of ...

What are these

good for?

data goldmine

Service Execution

Domain

Expert /

Developer

Service-

requesting

Actor

RWK Model

Adp.

Hypothesis

ML trained

algorithm

Service Request

(maintain room comfort)

Service Execution

Request

CVO

observers

CTRL PLANE

RWK Model

RED: associated with RWK

modeling

CHANGING THE RWK MODEL

DE for SK

DE for RWK

Observed

(and Actuated)

RW Entities

Observed

(and Impacted)

Actor

Real

World

Sensor

Source

Data Source/Sink Virtualization

Sensor Source

Sensor

Source

Actuator Sink

Virtual

Sensor

Virtual

Actuator

Service Execution

Hut.

Virtual Sensor

Cor.

Adp.

RWK Validation CVO

Execution CVO

Actuate

VOs

DATA PLANE

FB1 FB2

qr

s

p

CVO

observers

EXEC PLANE

BLUE: associated with

CVO / VO

CHANGING THE ROOM

CONDITIONS

SK ModelSK Validation

CVO

Some examples please?

• tracking cars in a smart city

• medical equipment tracking and asset

management

tracking cars in a smart city

Best demo

award at

FuNeMS 2013

courtesy of Marc Roelands (Bell Labs – Alcatel Lucent)

more info: http://www.iot-icore.eu/attachments/article/66/iCore_FuNeMS%2713_ALU.pdf

tracking medical equipment

Validate

Train

Execute

RWO parameter reconfiguration

recommendations to improve energy

efficiency of location sensorsIn the demo implementation,

Database of location

information(spatial &

temporal) of objects

3

4

5

Train efficiency of location sensorsIn the demo implementation,

location data of objects is

simulated

1

2

2a4a

6

7

8

Trento Hospital S. Chiara

Trilogis + ZIGPOS

where are we heading?

• connected things will be able to “socialise”

their status (i.e. friends by ownership)

– relevance, proximity based discovery and

selectionselection

• integration with existing “human” social

networks

– spontaneous service provisioningL. Atzori, A. Iera, G. Morabito From “Smart Objects” to “Social Objects”: The Next

Evolutionary Step of the Internet of Things IEEE Communications Magazine, Jan 2014

B. Kim, T. Kim, D. Lee, and S. J. Hyun, "SpinRadar: A Spontaneous Service Provision Middleware for

Place-aware Social Interactions," PERSONAL AND UBIQUITOUS COMPUTING, April 2013

cloud and IoT for big-data “avoidance”?

• tackling the other potential bottlenecks (wise use of network

resources and resource constrained nature of IoT)

• need to ensure robustness for IoT

• low-latency services

• high-interoperability• high-interoperability

• use of edge cloud technology and distributed data processing

Data

Sources

Data to Apps:

Hadoop and batch

processing

Data

Sources

Apps requirements:

live stream (processing

“guidelines” travel opposite

compared to data)CBA

transmitted data sizes

da

ta fro

m 5

0b

ln d

ev

ices

edge processing loaded network

application domains

da

ta fro

m 5

0b

ln d

ev

ices

network

networkingcomputation

Conclusions

• Internet of Things is part of our present

• efficient usage of planet Earth resources is a

challenge with growing and aging population

• tremendous growth potential (50bln only 3% • tremendous growth potential (50bln only 3%

of all objects :-)

• there is work to do

Further info / links

[REF2] P. Vlacheas, R. Giaffreda et al. "Enabling Smart Cities Through

a Cognitive Management Framework for the Internet of Things“,

IEEE Communications Magazine - Special Issue on Smart Cities (June

2013)

[REF1] IERC April 2013 Newsletter – Foreword (see THIS LINK)

[REF3] iCore website (www.iot-icore.eu/latest-news) [REF3] iCore website (www.iot-icore.eu/latest-news)

Best Demo Award at FuNeMS 2013

Thank you!

Raffaele GiaffredaSmart IoT (RIoT) Research Area Head

(CREATE-NET)

EU FP7 iCore Project CoordinatorEU FP7 iCore Project Coordinator

raffaele.giaffreda@create-net.org

Websites:

www.create-net.org/research/research-areas/riot

www.iot-icore.eu