Korea EU workshop - solutions and challenges for a Cognitive IoT

Internet Connected Objects for Reconfigurable Eco‐systems

iCore EU FP7, project No 287708

iCore cognitive framework: results and challenges ahead for a Smart IoT

Raffaele Giaffreda, iCore Project Coordinator(CREATE‐NET)

Seoul, 30 Sept 2013

Abstract Abstract: forecasts about the number of connected devices by 2020 all point to

billions of networked objects. As these numbers increase, there will be growing need to dynamically interpret and filter the wealth of information such widely distributed objects will produce, to prepare it and make it useful also across application domains preventing stovepipes at data level and fostering IoT‐based innovation. iCore project started contributing solutions to this problem, from virtualisation of objects to address heterogeneity, moving to means to gather Real World Knowledge via IoT objects and influence decision‐making in different application domains. The presentation will show some of the results achieved in iCore and will expose the yet unaddressed challenges in the domain of solutions that bridge IoT, Cloud and Big Data.

Research Interest and Need for Collaboration: reliable IoT services for Smart Cities: the role of broadband access and cloud computing; IoT distributed monitoring as Big Data generator: use of cognitive technologies for data filtering and interpretation.

wealth of sensing data

data

data

data data

data

data data

data

data

datadata

datadata

SE

NS

ING

data

H/W

Real World Objects (RWO)

unlocking a huge potential

data

data

data data

data

data data

data

data

datadata

datadata

data

H/W

presence

patterns exist ...

SE

NS

ING


it’s a complex IoT world...

how to address (some of) these problems?

data

data

data data

data

data data

data

data

datadata

datadata

data

H/W

presence

patterns exist ...

SE

NS

ING


the iCore solutions

data

data

data data

data

data data

data

data

datadata

datadata

data

H/W

Real World Knowledgepresence

System Knowledge

derive patterns of ...interpret data

from data to knowledge

S/W

(RWK) Models

(SK) Models

SE

NS

ING


CVO Management Unit

Real World Knowledge/Model

API

Service Request Analysis

iCore User Preferences

VO FactoryVO TemplateRepository

Service TemplatesRepository

System Knowledge/Model

Service Execution Request

CVORegistry

CVO TemplatesRepository

VORegistry

VOContainer VO OVOVO VO VO Front End

VO Back End: RWO Driver

CVO Factory

Device manufacturer

API

Data ProcessingDomain Expert / Developer

API

Domain Expert / Knowledge Engineer

API

Device Installer

VO Management Unit

iCore User

API

Service Request

RWK

Desig

n& Store

VO Data Session

iCoreSystem Operator

API

CVO Tem

plate

Desig

n & Store

API

API

User Profiling

System

Adm

inistratio

n &

Man

agem

ent

System

Adm

inistratio

n &

Man

agem

entVO Execution Request

RWK Update

Situation Modelling

People modelling

Natural Language Processing

CVO Container (Execution)CVOCVOCVOCVOCVO CVO

Situation Observer

the iCore Architecture


Cognitive Inside where and why... Service Level: gather data relate to actions / situations

and support users (OBSERVE – LEARN – REPLACE) routine jobs (watering plants, feeding the fish, taking pills, switch on/off lights)

non‐expert alerts (a fire, a leak, a fault)

Composite Virtual Object: instrumental in guaranteeing more robust IoT Services. ability of adding redundancy for fault‐tolerance approximate services

Virtual Object: create a virtual counterpart for objects address heterogeneity problems manage sensor energy and communication resources

Cognitive Inside – take‐away messages

more reliable and interoperable IoT

(RWK) Models

(SK) Models

more resilient IoT

more dependable IoT

support users of future Smart Cities applications

(routine + alerts)

IoT reliability and durability through VOs

IoT resilience and fault tolerance

Planned iCore trials Tracking of medical equipment in big hospitals (Trento – Italy)

Smart Santander integration + smart tourist (Santander – Spain, Athens – Greece)

CBRN Security trial (Thales – France) Theme Park (China)

any potential opportunities for South Korea collaboration?

Further info / links

[REF2] P. Vlacheas, R. Giaffreda et al. "Enabling Smart CitiesThrough a Cognitive Management Framework for the Internetof Things“, IEEE Communications Magazine - Special Issueon Smart Cities (June 2013)

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

[REF3] iCore website (www.iot-icore.eu/latest-news) Best Demo Award at FuNeMS 2013

IoT, Cloud and Big Datathe challenges ahead...

Big data: “big” relates to the huge number of data sources have data, patterns exist Need to purposefully aggregate data scaling‐up use of machine learning is a challenge...

Cloud: constrained devices and limited scope for data processing dynamic deployment of data‐processing resources on the data‐source data‐consumer path is a challenge...

IoT Networking: delivery of “object‐produced” data M2M traffic and dynamic deployment of connectivity resources is a challenge...

Thank you!

Raffaele GiaffredaiCore Project Coordinator

raffaele.giaffreda@create‐net.org

Website: www.iot‐icore.eu

iCore EU FP7, project No 28770815

Korea EU workshop - solutions and challenges for a Cognitive IoT

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