Internet of Things Vision and the Technology Behind Connecting the Real, Virtual and Digital Worlds
Olaf Østensen
Statens kartverk
GEOINFO 2011 4. oktober, Uppsala
Basert på bidrag fra:
Dr. Ovidiu Vermesan,
Dr. Arne-Jørgen Berre,
begge fra SINTEF
Future Internet
The vision of Future Internet based on standard
communication protocols considers the merging of
computer networks, Internet of Media (IoM), Internet of
Services (IoS), Internet of Things (IoT) into a common
global IT platform of seamless networks and networked
“things”. This future network of networks will be laid out as
public/private infrastructures and dynamically extended
and improved by terminals created by the “things”
connecting to one another.
0537.84.61261
The Future Internet will have…
a considerable higher transmission capability
a computational capacity and performance that clearly will exceed what we have today
wireless access everywhere
a great number of different digital objects and electronic devices connected
integrated security mechanisms at all levels and adaptive tools and services
The political agenda
INSPIRE, SEIS, …, Digital Agenda for Europe
Digital agenda for Europe
Interoperability solutions for European Public Administrations
INSPIRE technical architecture - the infrastructure built by member states
Very structured, but …
Spatial data set – spatial data service - centric
Only member state level
Service
Metadata
Data Set
Metadata
Discovery Service
Application and Geoportals
InvokeSD
Service
Spatial Data Set
View
Service
Download
Service
Data
Layer
Serv
ice
Layer
Ap
pl.
Layer
Transf .
Service
Spatial Data Services
Harmonised SpatialData Services
Registers
Registry Service
Service Bus
GeoRM layers
The future infrastructure?
Things
Data, services,
models, applications,
sensors
Cloud computing –
non-cloud computing
Free and open source
– licenced
Public - private
Things are identifiable
Things are invokable
Things have interfaces and can communicate
Things have metadata - semantics
Need standards
Need frameworks
Future Internet
IoT – Internet of Things
IoM – Internet of Media
IoS – Internet of Services
IoE – Internet of Enterprises
Internet of Things
Internet of Things is an integrated part of Future Internet.
Source: Internet of Things - Strategic Research Roadmap, CERP-IoT 2010
A dynamic global network infrastructure with self configuring
capabilities based on standard and interoperable
communication protocols where physical and virtual “things”
have identities, physical attributes, and virtual personalities
and use intelligent interfaces, and are seamlessly
integrated into the information network.
In the IoT, “things” are expected to become active
participants in business, information and social processes
where they are enabled to interact and communicate
among themselves and with the environment by
exchanging data and information “sensed” about the
environment, while reacting autonomously to the
“real/physical world” events and influencing it by running
processes that trigger actions and create services with or
without direct human intervention.
Internet of Things
Source: Internet of Things - Strategic Research Roadmap, CERP-IoT 2010
Interfaces in the form of services facilitate interactions with
these “smart things” over the Internet, query and change
their state and any information associated with them, taking
into account security and privacy issues.
Internet of Things
Source: Internet of Things - Strategic Research Roadmap, CERP-IoT 2010
Connect objects and devices to repositories and networks using
simple, and cost effective systems of item identification so data about
things can be collected and processed.
Ability to detect changes in the physical and environmental status of
things, using sensor technologies.
Internet of Things
Devolving information processing capabilities to the edges of the
network using embedded intelligence in the things.
Miniaturization and use of nanotechnology so smaller and smaller
things will have the ability to interact and connect.
Internet of Things
Connecting:
A symbiotic interaction among the real/physical, the digital, virtual worlds and society
Things Attributes
“Things” can initiate communication
“Things” can communicate with other “things”, computing
devices and with people
“Things” can be “real world entities” or “virtual entities”
“Things” have identity; there are means for
automatically identifying them
“Things” may have sensors attached, thus they can
interact with their environment
“Things” can collaborate to create groups or networks
“Things” can do many tasks autonomously
“Things” are involved in the information exchange
between real/physical, digital and virtual worlds
“Things” can selectively evolve and propagate
information
Things Attributes
“Things” would be competing with other “things” on resources, services and subject to selective pressures
“Things” can create, manage and destroy other “things”
“Things” can use services that act as interfaces to “things”
“Things” respect the privacy, security and safety of other “things” or people with which they interact
“Things” use protocols to communicate with each other and the infrastructure
“Things” can negotiate, understand and adapt to their environment
“Things” can extract patterns from the environment or to learn from other “things”
“Things” are environmentally safe
“Things” can take decisions through their reasoning capabilities
Ubiquitous Sensor Network
Any place, any thing using wireless tags/nodes-Ubiquitous
Sensing ID and environmental information-Sensor
Real time monitoring and control using a-Network
IoT and Cloud Computing
Computing paradigm where data and services reside in
massively scalable data centers and can be ubiquitously
accessed from any connected device over the Internet.
Physical location and underlying infrastructure details are
transparent to users
Anytime, Anywhere access to IT resources delivered
dynamically as a service
IoT and Cloud Computing
Real virtual and digital worlds
Connecting real, virtual and digital worlds
The challenge:
Linking smart wireless identifiable devices and RFID data with
virtual worlds software programs
Transfer positions of real persons and real things into the
virtual world.
Enable the smart wireless devices to trigger actions in the
real world.
Source: Dell
Residents can go to the virtual factory,
customize their Dell and purchase, and
their PC arrives at their real-life door.
“Connecting virtual reality with real world commerce"
“Connecting Consumers Virtual Lives with Their Real World Needs”
Wireless Smart System Applications
Automotives
Aeronautics
Information and Telecommunication (ITC)
Medical Technologies
Logistics and object mobility and management
Chrysler
IoT Application Domains
Aerospace and aviation,
Automotive,
Telecommunications,
Intelligent Buildings,
Medical Technology, Healthcare,
Independent Living,
Pharmaceutical,
Retail, Logistics, Supply Chain Management,
Manufacturing, Product Lifecycle Management.
Oil and Gas
Safety, Security and Privacy,
Environment Monitoring,
People and Goods Transportation,
Food traceability,
Agriculture and Breeding,
Media, entertainment and Ticketing,
Insurance,
Recycling.
ITS (EU CVIS)
Execution infrastructure ( OSGi based)
Basic Facilities Domain Facilities
Services
Communication Infrastructure
(including OS and Hardware (sensors, actuators etc) )
Native / Real - time
applications
Security
Life
cycle DDS
Connection
Manager
HMI HMCA Billing&
Payment
Position&
Map matching Map
Provision
Native
Interface
…
Dangerous
Goods
Parking
Zones
Flexible
Bus Lane Enhanced
Driver
Awareness
Routing
Network
Assessment Coop.
Travelers
Assistance
Access
Control Traffic Control
Assessment
Coop.
Traffic
Information
Coop
Monitoring
Vehicle/
Roadside
Tree
Priority
Information
Coop.
Traffic
Control
Broadcast Dep &
prov
Identity
Location
Reference
GSP
Speed
Profile
Crisis management (DiVA FP7)
23
Crisis team
Smart Homes
24
Smart Cities
Smart City case study. A smart city conveys a set of networked smart applications and
services supporting citizens in performing their leisure and professional
related tasks (Picture of Dongtan, a smart city located 40 km from Shanghai, China).
Standards and technologies
UML, SoaML, Webservice standards (WSDL, SOAP...)
Extend and add technologies to better managing service
enablement of things (e.g., ThingML)
ISO 19100-series of geographic information/geomatics
standards
OGC services standards
Observations & Measurements (O&M) - The general models and XML
encodings for observations and measurements. (also ISO 19156)
Sensor Model Language (SensorML) - standard models and XML
Schema for describing the processes within sensor and observation
processing systems.
Sensor Observation Service (SOS) - Open interface for a web service to
obtain observations and sensor and platform descriptions from one or
more sensors.
Integrate methods and tools to provide an integrated
construction and execution framework for service enablement
of things 26
One of the “things” – models as services (MaaS)
Design time
Set-up time
Execution time
• Discover existing resources
• Build the modeling workflow
• Register/Annotate the new Service
• Discover existing Modeling Services
• Select a region of interest
• Discover existing data sources
• Select the data sources
• Set the parameters
• Play the scenario
• Discover existing Modeling Services
• Select a region of interest
• Discover existing data sources
• Select the appropriate sensors data streams
• Select functional parameters for the alerting system
Semantic Annotations are a key enabler for discovery of services!
(provide on-the-shelf modeling solutions)
(connect the appropriate sources of
information to feed the modeling service)
(interact with the information provided by
the models and monitor the system)
A General Scenario for MaaS – User Operations
Oil Spill Pilot Case: Impact
Difficult decisions ahead!
A clear need for risk
analysis tools to support:
• strategic,
• tactical, and
• operational
decision-making
29
05.10.30
dissolution from entrained droplets
degradation
surfacing of droplets, slick formation
particulate adsorption/desorption
settling
Volatilization from water to air
sediments: deposition, dissolution, degradation
Response actions
Surface processes:
• drifting, spreading
• natural dispersion
• emulsification
• evaporation
• stranding
Oil spill processes
Biological effects
Scenario – Oil Spill Risk Analysis
31
How to set up Web services that can be manipulated by non-technical operators
and can enable a quick and adequate response in order to minimize biological
consequences of oil spills at sea?
Source: SINTEF
32
ENVISION – An Infrastructure for MaaS
ENVIronmental Services Infrastructure with ONtologies
Portal with a pluggable decision
support framework
Visual service chaining
Migration of existing models to MaaS
Semantic annotation infrastructure
Visual semantic annotation
mechanism
Multilanguage ontology management
Execution space
Semantic discovery catalogue
Semantic service mediator
Adaptive service chaining execution
05.10.33
Current architecture
Map
database
Sea depths;
shorelines;
sediment types NMA
Currents;
wind
met.no
PredictOilDrift
Spill data (location; date; amount; oil type)
Weather
and sea
models
Oil drift predictions (4D)
Cod
spawning
areas IMR PredictCodEffects
WAF WAF
concentrationconcentration
fieldfield
VerticalVertical sectionsection
KeysKeys
WindWind vectorvectorMassMass BalanceBalance
HomeHome
base for base for
responseresponse
equipmentequipment
DispersantDispersant
helicopterhelicopter en en
routeroute
SkimmersSkimmers
ClockClock ((days:hoursdays:hours: : minutesminutes))
WAF WAF
concentrationconcentration
fieldfield
VerticalVertical sectionsection
KeysKeys
WindWind vectorvectorMassMass BalanceBalance
HomeHome
base for base for
responseresponse
equipmentequipment
DispersantDispersant
helicopterhelicopter en en
routeroute
SkimmersSkimmers
ClockClock ((days:hoursdays:hours: : minutesminutes))
ENVISION
end user
Map
database
Weather
and sea
data
Mode selection (real-time/historic)
met.no/
SINTEF
<forecasts>
<historic data>
Citizens and private sector
Public sector, national and European
ND - service based infrastructure
metadata
WMS - view services
Download - WFS services
Data sources for the pilot
05.10.35
Map data
- basic map
Map data
- included depths
Data sources for the pilot
36
Weather data
- wind direction
and strength
Weather data
- included air
pressure
05.10.37
New architecture – model as a service
Map
database
Sea depths;
shorelines;
sediment types NMA
Currents;
wind
met.no
PredictOilDrift
Spill data (location; date; amount; oil type)
Weather
and sea
models
Oil drift predictions (4D)
Cod
spawning
areas
IMR PredictCodEffects
WAF WAF
concentrationconcentration
fieldfield
VerticalVertical sectionsection
KeysKeys
WindWind vectorvectorMassMass BalanceBalance
HomeHome
base for base for
responseresponse
equipmentequipment
DispersantDispersant
helicopterhelicopter en en
routeroute
SkimmersSkimmers
ClockClock ((days:hoursdays:hours: : minutesminutes))
WAF WAF
concentrationconcentration
fieldfield
VerticalVertical sectionsection
KeysKeys
WindWind vectorvectorMassMass BalanceBalance
HomeHome
base for base for
responseresponse
equipmentequipment
DispersantDispersant
helicopterhelicopter en en
routeroute
SkimmersSkimmers
ClockClock ((days:hoursdays:hours: : minutesminutes))
ENVISION
end user
Map
database
Weather
and sea
data
Mode selection (real-time/historic)
met.no/
SINTEF
<forecasts>
<historic data>
New: Spill data entered by user
(instead of satellite link) Support for both real-time
and historic modes A (simple) PredictEffects
MaaS can be built to demonstrate model chaining
MaaS - WPS
service
service
service
service
Additional data sources for decision support
Ship traffic
- identity
- direction and
speed
- cargo
Other data - examples
- emergency installation
- protected area
- cultural value
Additional data sources for decision support
39
Environmental data
- birds
- areal classification
Other data - examples
- outdoor life
- fishing farms
05.10.40
New architecture – model as a service
PredictOilDrift
Oil drift predictions (4D)
PredictCodEffects
WAF WAF
concentrationconcentration
fieldfield
VerticalVertical sectionsection
KeysKeys
WindWind vectorvectorMassMass BalanceBalance
HomeHome
base for base for
responseresponse
equipmentequipment
DispersantDispersant
helicopterhelicopter en en
routeroute
SkimmersSkimmers
ClockClock ((days:hoursdays:hours: : minutesminutes))
WAF WAF
concentrationconcentration
fieldfield
VerticalVertical sectionsection
KeysKeys
WindWind vectorvectorMassMass BalanceBalance
HomeHome
base for base for
responseresponse
equipmentequipment
DispersantDispersant
helicopterhelicopter en en
routeroute
SkimmersSkimmers
ClockClock ((days:hoursdays:hours: : minutesminutes))
MaaS - WPS
service
service
service
service
New: Prediction model as service Input data to model as services Oil spill decision portal Additional input to portal as
services
Oil spill – decision support
portal
Oil spill
Weather
Map
Environment
Other …
service catalogue
service
service
service
Oppsummering
… mens vi møysommelig bygger vår infrastruktur med
dagens og gårsdagens teknologi …
… kommer nye teknologier og paradigmer i stadig økende
fart …
… og muliggjør en langt rikere infrastruktur i framtida …
… med ny funksjonalitet og nye muligheter …
… men også utfordringer til sikkerhet, personvern og
tilgjengelighet for alle …
Hvor står vi om 10 år?
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