Medical Internet of Things (MIoT) & Imbedded Intelligence in Healthcare

Dr. Abdelbaset Khalaf khalafb@tut.ac.za 3rd GFMD-WHO

Medical Internet of Things (MIoT) rate

•  Integra)onofmedicaldevicesinanetworkconnec)on•  Networkcanbemanagedfromtheweb•  Provideinforma)oninreal)me•  Communica)on:persontoperson(P2P)&machineto

machine(M2M)•  Allowinterac)onbetweenhealthprofessionals&pa)ents•  MIoTcanbeseenfrom3paradigms:Ø  Internet-orientedmiddlewareØ  ThingssensorsorientedØ  Knowledge-orientedseman)cs

InternetProtocol

Number/Address

Number/Address

5RIRs

LIR/ISPs

EndUsers

IPAddressesconnecttheInternet

UnderstandInternet:IPAddressing

IPv4AddressSpaceIssued:RIRstoCustomers

(Jan.1999–Dec.2008)Source:INRStatusReport(NRO,Asof31Dec.2008)byHZhaoITU

0

1

2

3

4

5

6

IPv4AddressSpaceIssuedbyyearFixedlength,32bitscheme,morethan

4billion(232)addresses

IPv6Greatlyexpandedaddressspace

(2128)Moreattractivefor

futureInternetapplicationscomparedtoIPv4

Potentialsocio-economicbeneZitsfor

ubiquityoftheInternet

MultiAccess:Enhancedlifemobility

IPNextGenerationProtocolIPv6Addresses2128=3.40282x1038

IPv4:Fixedlength,32bitscheme,morethan4billion(232)addresses

EmergenceofmobilesasplatformforwirelessInternetaccessespeciallyindevelopingcountrieswillputmorepressureontheIPaddressspace

RequirealargerIPaddressspacetoenablewirelessnetworking&mobility

IPv6isemergingasthepreferredplaJormandisacorecomponentofthewirelessInternetarchitecture(3G&Beyond3G)

IPv6protocolprovidestheavailability&extensibilityofIPaddresses:Large-scalesensornetworks,IPSecurity,MobileIPv6,IP-basedMul)media

IPv6Deployment:EssentialforwirelessInternet

Internetisnowacriticalglobalinfrastructureforsocio-economicdevelopmentandgrowingfasterindevelopingcountries

Embedded Intelligence

Technical Integration

Industry Collaboration

Embedded Intelligence in Healthcare Proximity

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Virtualization Faster time to market

New markets

Business Transformation

Healthcare Applications

Low latency

Quality of Experience

Revenue generation

Cloud

Network Standards

Product monitoring

Disease detection

Improve care plans

Helping doctor A

Device Sensor Data

IoT Applicat ion/ Data Store

Advanced Analyt ics / Pattern Recognit ion/C l a s s i f i c a t i o n s /

Optimizat ion

Insights / Act ion Inte lligence

Embedded Intelligence in M-IoT

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•  Growth at a high rate exceeding 7% •  Estimated Revenues by 2020 $2.2 trillion

•  Healthcare is one of the Leading industries

Embedded intelligence is the ability of a product , process or service to monitor its -  Operational performance, -  usage load, -  environment

Goals: -  enhance performance and lifetime, -  increase quality and -  improve customer satisfact ion.

What is it? How does it help? -  Monitor health and usage of products

to extend their performance and lifet ime

-  Improve market appeal and acceptance of products

-  The ability for a service, system or product to be used by ageing and people with special needs.

-  Address skills shortages in limited resources -  Enabling new revenue opportunities

Edge Fog Data in Motion

Cloud Historic/Predict ive Analytics

Device to device communicat ion

More interact ion and response

More comput ing

HealthcareDevices&Systems

Artificial Intelligence (AI) on the Edge Supported by Fog/Cloud

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Putting It All Together

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Scenario: Intelligent MRI Machines

Failure Event Pattern Matching Algorithm

Imaging System -  MR imaging controls

Patient Data -  Body part for scan -  Weight of patient

Magnetic Field Control - Manual setting of magnetic

field required for scan as prescribed by the doctor

Onboard Sensors - Captures temperature at various

positions on MR Machine

Data Acquisition System

Other data sources q Equipment history q Maintenance records q Environmental data q Expected failures q Maintenance Schedules

Optimisation Models q Predictive Asset

Maintenance

q Scan Data q System

Failure Logs

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Predictive Analytics Platform

SystemHealthDashboardPredic)veAssetMaintenance

Example: Architecture of System

TUT/FSATI 2017

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Success Requirements: Are we ready? Watch the outcome of Horizon 2020:eHealth workforce development

•  Thecoreofanyhealthcaresystemisitsworkforce•  Healthcaresystemrequiresarobustsupplyofhighlyskilled

professionals•  AndtheymustbedigitallyskilledineHealthØ  ThefuturestateofhealthcaredependsonworkforcewitheHealth

skillsØ  Howcanweaddressworkforceshortageandthelackofaccessto

skills/competenciesineHealth/healthIT?v  Weneedtomapandquan)fyneeds&supply,demands&trendsfor

skills&competenciesforalleHealthactorsv  Thewayforward:gapanalysis,casestudiesandstakeholders

engagementtoformbiggerpictureofeHealthworkforcev  DevelopmentofeHealth/HealthITcourses/curricula

Current developments and research domains •  BodySensorsNetworkBSNapplica)ons•  Energy-efficiencyforBSNs•  SecurityandprivacyforBSNs•  BSNsystemarchitecture•  Interferencemi)ga)oninBSNs•  Systemsenablingpa)entself-monitoringandassessment•  HardwareforBSNs•  BSNswithCloudCompu)ngCapabili)es•  BSNsforeHealthandac)vitymonitoring/biomonitoring•  BSNsandwearables•  Brain-2-BrainCommunica)on•  BSNsandtheInternetofThingsBrain-2-Braincommunica)on•  Expertsystemsforillnessdiagnosisinlimitedresourcescountries