Space Efficiency + Spectral Efficiency =MAZE OF TINY, CONNECTED THINGSTrend: more and more widespread sensing and monitoring data available...Tiny but Powerful devices
what’s beyond IP connectivity?The Internet parallel...HTTP/WWWsearch enginesconnect your infoTCP/IPHTMLrepresent info / aggregate infoWWWpersonalised knowledgecollections, blogs...The Semantic Webfind infoVALUE!
IoT, what’s beyond IP connectivity?early stages for the IoT...HTTP/WWWhundreds of bespokeIoT applicationsThe Semantic WebVALUE!personalised knowledgecollections, blogs...represent info / aggregate infosearch enginesconnect your infoTCP/IPHTMLWWWfind infoobjecttoday
HUMANMACHINEIoT innovation potential...“Innovation”: onecan focus on apps!!!OBDOn Board DiagnosticsMACHINEHUMAN
siloed and bespoke IoT applicationsAPPSHOUSEAPPSFRIDGEAPPSPATIENTAPPSPATIENTAPPSAPPSAPPSAPPSAPPSAPPSDATA / INFORMATION OVERLOAD, BUT...CARSENSORSHOUSESENSORS FRIDGESENSORSPATIENTSENSORSPATIENTSENSORSPATIENTSENSORSPATIENTSENSORSPATIENTSENSORSPATIENTSENSORSAPPSPATIENTSENSORSAPPSTRUCKSENSORSAPPS
IF A WELL-DEFINED INTERFACE INTO CAR SENSORS BRINGS SUCH POTENTIAL...APPSHOUSEAPPSFRIDGEAPPSPATIENTAPPSPATIENTAPPSAPPSAPPSAPPSAPPSAPPSCARHOUSEFRIDGEPATIENTPATIENTSENSORSPATIENTSENSORSPATIENTSENSORSPATIENTSENSORSPATIENTSENSORSAPPSPATIENTSENSORSAPPSTRUCKSENSORSAPPSSENSORS SENSORS SENSORS SENSORS
iCore concepts• Virtual Object• Composite VirtualObject• Service / User Level• Service / User Level
Virtual Object as OBD across silosIoT servicesVirtual Object SW AgentIoT servicesVO registryTo upper iCore levels and InternetSemantic VO descriptionsAbstractionICT objects(heterogeneous world)Sensors and actuatorsProprietary services IoT servicesAssociated physical objectsAbstraction17
what ingredients?• common interfaces to interact withobjects (i.e. REST)• + extra containers for metadata• let the systems know what the object• let the systems know what the objectis good for, its location (“I am a Tempsensor in Room A”), its accuracy, itsenergy levels etc.replicate what the HTML (HyperText Markup Language)has done for simply connected info“I am a webpage and I talk about Paris history”
WHAT ARE VOs GOOD FOR?• OBJECTS PROXIMITY– automated selection “by relevance” (see argumentsfor cognitive technologies in a minute...)• OBJECTS REUSE• OBJECTS REUSE– reuse across different apps, increase availability,hence, increase monitoring / sensing granularity• OBJECTS MGMT– i.e. energy management, contextualised sensing(accuracy vs. sensing frequency) etc.Providing IoT systems the ability to self-configure, based on various requirements, and ...
...providing IoT systems the ability to adaptCARAPPSHOUSEAPPSFRIDGEAPPSPATIENTAPPSHOUSEFRIDGEPATIENTSENSORS SENSORS SENSORS SENSORSPATIENT is near the FRIDGECAR is near the HOUSEPATIENT is driving the CARobjects reuseacross domainsKitchenPresDetect PatientStatusDetectEasy for us...not for a “dumb” computer...
lesson #2• connect your objects across domains, unlockfurther value
Internet vs. IoT• a page + a page + a page...connect info• represent info – HTML• aggregate info – hyperlink• a (sensor) feed + a feed + a feed...• represent feeds – VO• aggregate feeds – CVO
the need for cognitive technologies• iCore Composite Virtual Object (CVO)– aggregation of simple sensing capability– self-maintenance (service maintained in case offailure) increased sensing granularity needed!failure) increased sensing granularity needed!– System Knowledge• what is available to meet reqs?“smart but not so much...”ability to select alternatives based onwhat metadata we put in the extra VOcontainersCT 1
the need for cognitive technologies• iCore Service Level and overall CognitiveManagement FrameworkCT 2,3
use of cognitive technologies in the IoT• Build models for Real WorldKnowledge representation• Help predict based on observationof past (training)• Assist rather than replace human• Assist rather than replace humandecisions• Personalise the behaviour of IoTsystems to tailor user changingneeds and situations
Putting it all together, iCore Cognitive Mgmt FrameworkService LevelServiceExecutionRequestServiceRequestselect, notificationServiceRequestAlert / PredictACKApplicationCVO LevelVO LevelCVO/VOExecutionRequestRWOinteractionsselect,deploy(bind), runset ofrunningprocessessatisfyingServiceRequestnotificationaccordingto servicetemplateACKRWOsdynamicbinding
Internet vs. IoT• find info• personalised knowledge collections, blogs as“ready info meals”...• find VOs / CVOs• personalised IoT services, applications thatlearn how to assist users
the need for cognitive technologies• factoring “smart logic algorithms” out of developersconcerns– IF “crash” THEN “alertRSA”– “crash” (IF VO_x = TRUE THEN crash := TRUE)– (IF VO_x = TRUE AND VO_y = TRUE THEN crash := TRUE)TAG:crashdetectVO_xTAG:crashdetectVO_yIF (VO_x = TRUE) AND (VO_y = TRUE)THEN crash := TRUEIF VO_x = TRUETHEN crash := TRUEIF (VO_x > TH_x) AND (VO_y > TH_y)THEN crash := TRUEfactor out cognitive technologiesCT 2• iCore community: foster “ready meals” for IoT apps
the need for cognitive technologies• rather than for the selection of appropriate templates,here focus is on refinement of selected one accordingto observed system-reality matching• Real-World-Knowledge “growing”• Learning and adaptation to the users preferences• Learning and adaptation to the users preferencesTAG:crashdetectVO_xTAG:crashdetectVO_y IF (VO_x > TH_x) AND (VO_y > TH_y)THEN crash := TRUECT 3assessQUALITY ofPREDICTIONREFINETH_x, and TH_y
iCore Architecture, RWK grow and SK growService LevelServiceExecutionRequestServiceRequestselect,Delta (RWK-RW)ACKApplicationRWKModeltweakparameters /algorithmsCVO LevelVO LevelCVO/VOExecutionRequestRWOinteractionsselect,deploy(bind), runset ofrunningprocessessatisfyingServiceRequestACKRWOsRWKSKDelta (SK-S)SKModelPersonalised RWK and SK...
in one slidesrv templates(RWK models)srv templates(RWK models)srv templates(RWK models)CVO templates(SK models)instantiation of same cognitive algorithms linking sensorsgets tailored with usage to produce outputs and alerts thatmatch user preferences, situation, infrastructure contextCVO templates(SK models)CVO templates(SK models)
iCore and Cognitive Technologies• CVO Level “system knowledge”– SLA-driven VO selection / maintainance– semantic enrichment semantic-based reasoning– selection by relevance to the needs of the application• deal with data / information overload– template selectSummaryCT 1– template select– given VO / CVO “types” find best algorithms that combine thesefor desired output• deal with data / information overload– learn and predict– given an algorithm, tweak parameters to better align iCoresystem behaviour to the observed real situation– Real World Knowledge (RWK) “growing”, adaptation to userpreferencesCT 2CT 3
The Internet of Things evolution timelineThe Dumb IoT The Craft IoT The Cognitive IoTYESTERDAY TODAY TOMORROWThe Dumb Internet The Craft Internet The Technicolor InternetThe Dumb IoT The Craft IoT The Cognitive IoTBear with us, we are building it!
references• iCore application in smart-cities and IoT-basedmonitoring[REF1] P. Vlacheas, R. Giaffreda et al. "Enabling Smart Cities Througha Cognitive Management Framework for the Internet of Things“,to appear in IEEE Communications Magazine - Special Issue onto appear in IEEE Communications Magazine - Special Issue onSmart Cities (June 2013)[REF2] IERC Newsletter April 2013 – foreword by R. Giaffreda
thank you!iCore Websitewww.iot-icore.euContacts:Raffaele Giaffredaraffaele.email@example.com yrs EU FP7 Integrated Project(started 1st Oct 2011)20 Partners with strong industrialrepresentation8.7mEur EU FundingEU + China and JapanID CardJapanraffaele.firstname.lastname@example.orgAbdur Rahimabdur.email@example.comEU + China and Japan