das internet der dinge -...
TRANSCRIPT
Das Internet der Dinge
Im Rahmen der Ringvorlesung Industrie 4.0
SS 2016, Universität zu Köln
Prof. Dr. Gregor Schiele FG Eingebettete Systeme der Informatik Uni Duisburg-Essen
Contents
1. What is the Internet of Things
2. Connected Devices Perspective
3. Connected Data Perspective
4. Conclusion
2
History
Term introduced 1999 by Kevin Ashton at Auto-ID Labs
Originally used to refer to a global network of RFID enabled objects
Many related terms: M2M Comm., Ubiquitous / Pervasive Computing, Cyber Physical Systems, Wireless sensor networks, IIoT, IoE, …
3
Definition: Internet of Things
“A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.” [ITU 2012]
4
[ITU 2012] International Telecommunication Unit: “Overview of the Internet of things”, Recommendation Y.2060, June, 2012
In Other Words…
Things connected to the Internet
That enable ‘advanced services’
5
‘Classical’ computer
‘Classical’ computer
‘Classical’ computer
Thing
Thing Thing
Thing
Thing
Thing
Thing
Thing Thing
The Internet
Internet Connected Things
An (IoT) thing is a physical object that is augmented with embedded electronics
Most basic thing: identifiable object (e.g. based on embedded passive RFID tags)
More advanced: sensing / smart object (e.g. based on embedded microcontroller, sensors / actuators and comm. interface)
6
7
8 http://www.tekreport.net/post/2016/02/26/smart-appliances
Chair of Information Systems II
Distributed Virtual Environments 9
Livescribe Echo Smartpen (2010)
10 Samsung NFC suit (2015)
Sensoria Fitness smart socks (2015)
Athos smart training clothes (2015)
fitb
it c
har
ge H
R (
20
15
)
UC Berkeley’s Smart Dust (2001)
Experimental system for autonomous sensing and
communication in cubic mm
Optical comm.
Using corner cube
retro-reflector and
steered laser
No commercial
solution (so far)
11
Networked Processors in Cars
12
http://www.heise.de/ct/03/14/170/
IoT System Overview
13
Smart Things IoT Gateways Online Services
Internet
Important Technology Trends
1. Computing
Miniaturization
Affordability
2. Sensing
Variety
Availability
3. (Wireless) Transmission
Communication
Energy transmission
14
One computer
(mainframe)
for many people
SIZE NUMBER
One computer
(PC) for
everyone
Many computers
for everyone
GPS receiver ZigBee transceiver
type: book name: DCOM author: Don Box
type: person name: Schiele gender: male
type: car name: XY-365 speed: 30 mph
25 °C
type: car name: GN-WK-1 speed: 30 mph
type: truck
name: AB-444 destination: Redmond load: 60%
type: person name: Jones gender: male
type: person name: Smith gender: male type: sensor
name: 144377 kind: temperature
type: book name: DCOM author: Don Box
type: person name: Jones gender: male
type: person name: Jones gender: male
Expected Business Impact of the IoT
Everybody agrees that the IoT will be huge...
McKinsey Global Institute: $2.7-$6.2 trillion
annually by 2025
General Electric: $32.3 trillion (46% of today‘s
global economy today) total worth
Cisco: $14.4 trillion net profit over next
decade
17
[source: M. Fell: Roadmap for The Emerging Internet of Things, carré & strauss, 2014, http://carre-strauss.com/documents/IoT_Roadmap.pdf]
IoT Market Opportunities
1. Data and process integration across full value chain and product lifecycle
2. New business models and services based on (seemingly) unrelated data
18
Hype Cycle for Emerging Technologies, 2015
19 http://www.gartner.com/newsroom/id/3114217
Two Views on IoT
Connected Things
Connected Data
20
vs
Contents
1. What is the Internet of Things
2. Connected Devices Perspective
3. Connected Data Perspective
4. Conclusion
21
Connected Devices
Everything becomes a smart object / thing
Things networked using Internet technologies (e.g. IP)
Things use Internet services to cooperate, i.e. the majority of users of services are devices and services instead of humans
22
[source: Cisco]
2003 2010
2015
2020
2020: 50 billion 2008: more devices than users in the Internet
users
devices
IoT: Connected Devices
IoT: Connected Devices
Topics include e.g.
Low power (machine-to-machine) networking
Ad hoc (system) auto configuration and self-organisation
Scalable Internet Infrastructure (bandwidth, number of devices, networks)
24
A Typical IoT Protocol Stack
25
CoAP / MQTT / XMPP
(TCP) UDP ICMP
IPv6 with 6LoWPAN
IEEE 802.15.4
HTTP / RTP
UDP TCP ICMP
IPv4 / IPv6
Ethernet / WLAN
TCP/IP Internet Stack: IoT Stack:
Hundreds / thousands of bytes Tens of bytes
Internet = IoT?
Established Internet protocols have been very successful
Why do we need new / modified ones?
26
A Typical Internet Device
High performance multicore 64bit CPUs
Gigabytes of RAM
Terabytes of HDD
Multithreading OS with standard TCP/IP stack
27
A Typical IoT Device
28 Adafruit FLORA (Arduino compatible) smart textile board
Low power 8bit microcontroller
Kilobytes of RAM & ROM
No / restricted OS support
Challenges
Data item sizes
Inefficient content encoding
Huge overhead, difficult parsing
Not optimised for energy saving
(Relatively) large buffers needed
Dedicated end-point addressing
Pull vs. push
29
A Typical IoT Protocol Stack
30
CoAP / MQTT / XMPP
(TCP) UDP ICMP
IPv6 with 6LoWPAN
IEEE 802.15.4
IoT Stack: CoAP: (binary) redesign of HTTP with push ability
MQTT: (loosely coupled) message queues
TCP typically too much overhead
6LoWPAN: adaptation layer for IPv6
802.15.4: low-power, low-cost, low speed, low range WLAN alternative
IEEE 802.15.4
Low range: 10 m
Low speed: up to 250 kbit/s
Low cost & power: ~10 times less than WLAN
Optimised for (infrequent) sending of small
(sensor) messages
31
802.15.4 Network Topologies
32
PAN coordinator Reduced function device
Communication flow
Adapted from: E. Callaway, P. Gorday, L. Hester, J. A. Gutierrez, M. Naeve, B. Heile: “Home Networking with IEEE 802.15.4: Developing Standard for Low-Rate Wireless Personal Area Networks”, IEEE Communications Magazine, August 2002.
Full function device
Star network Comm. only with PAN coord.
Peer-to-peer network Comm. with everyone in range
802.15.4 Channel Frequencies
33
Per Lab
Channel frequencies
(20 Kbps) (40 Kbps)
(250 Kbps)
Europe USA
From IEEE 802.15.4 to IEEE 802.15.4e 9
Ed Callaway, Paul Gorday, Lance Hester, Jose A. Gutierrez, Marco Naeve, Bob Heile, Home Networking with IEEE 802.15.4:
Developing Standard for Low-Rate Wireless Personal Area Networks, IEEE Communications Magazine, August 2002.
Since April 2009: 314–316 MHz, 430–434 MHz, 779–787 MHz bands in China (802.15.4c); 950–956 MHz band in Japan (802.15.4d); since August 2007 (IEEE 802.15.4a): ultra-wideband (UWB) PHY in 3 ranges: below 1 GHz, between 3 & 5 GHz, between 6 & 10 GHz.
Adapted from: E. Callaway, P. Gorday, L. Hester, J. A. Gutierrez, M. Naeve, B. Heile: “Home Networking with IEEE 802.15.4: Developing Standard for Low-Rate Wireless Personal Area Networks”, IEEE Communications Magazine, August 2002.
un
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sed
fre
qu
en
cy b
and
s
exte
nd
ed
to
30
ch
ann
els
in
80
2.1
5.4
-20
06
Worldwide
Contents
1. What is the Internet of Things
2. Connected Devices Perspective
3. Connected Data Perspective
4. Conclusion
34
Connected Data
Things (continuously) create data about their
physical surroundings
Data is made available on the Internet, i.e. the
majority of data is created automatically by
smart things instead of humans
Aka: big data
35
IoT: Connected Data
Topics include e.g.
Interoperable data models (e.g. RDF)
Data management and querying (e.g. CQELS)
Data analytics (big data)
36
Connected Data: Today
New content: 300h of video per minute
432,000h of video per day
236 TByte per day
164 GByte per minute 37
http://500px.com/photo/19080871
Problem: Data Size 43.9 Million PKW (Germany, 1.1. 2014)
3-4 GByte / min per PKW
154 PByte / min
0
20000
40000
60000
80000
100000
120000
140000
160000
Pkw D Youtube
0.164 TB/min
Tera
Byt
e /
min
(source: Kraftfahrt-Bundesamt)
Problem: Data Heterogeneity
39
http://www.flickr.com/photos/69730904@N03/8813574238/
Linked Data common
data models
(A) Solution: Linked Data
40
http://www.flickr.com/photos/69730904@N03/8813574238/
Linked Data
As of September 2011
MusicBrainz
(zitgist)
P20
Turismo
de
Zaragoza
yovisto
Yahoo! Geo
Planet
YAGO
World
Fact-
book
El ViajeroTourism
WordNet
(W3C)
WordNet
(VUA)
VIVO UF
VIVO Indiana
VIVO Cornell
VIAF
URIBurner
Sussex
Reading
Lists
Plymouth
Reading
Lists
UniRef
UniProt
UMBEL
UK Post-codes
legislationdata.gov.uk
Uberblic
UB Mann-heim
TWC LOGD
Twarql
transportdata.gov.
uk
Traffic
Scotland
theses.
fr
Thesau-
rus W
totl.net
Tele-
graphis
TCM
Gene
DIT
TaxonConcept
Open Library (Talis)
tags2con
delicious
t4gm
info
Swedish
Open
Cultural Heritage
Surge
Radio
Sudoc
STW
RAMEAU SH
statistics
data.gov.
uk
St.
Andrews
Resource
Lists
ECS
South-
ampton
EPrints
SSW
Thesaur
us
Smart
Link
Slideshare
2RDF
semantic
web.org
Semantic
Tweet
Semantic XBRL
SW
Dog
Food
Source Code Ecosystem Linked Data
US SEC (rdfabout)
Sears
Scotland
Geo-
graphy
Scotland
Pupils &
Exams
Scholaro-
meter
WordNet (RKB
Explorer)
Wiki
UN/
LOCODE
Ulm
ECS (RKB
Explorer)
Roma
RISKS
RESEX
RAE2001
Pisa
OS
OAI
NSF
New-
castle
LAAS
KISTI
JISC
IRIT
IEEE
IBM
Eurécom
ERA
ePrints dotAC
DEPLOY
DBLP (RKB
Explorer)
Crime Reports
UK
Course-
ware
CORDIS (RKB
Explorer)CiteSeer
Budapest
ACM
riese
Revyu
research
data.gov.
ukRen.
Energy
Genera-tors
reference
data.gov.
uk
Recht-spraak.
nl
RDFohloh
Last.FM (rdfize)
RDF Book
Mashup
Rådata nå!
PSH
Product Types
Ontology
ProductDB
PBAC
Poké-
pédia
patents
data.go
v.uk
Ox
Points
Ord-nance Survey
Openly Local
Open Library
OpenCyc
Open Corpo-rates
OpenCalais
OpenEI
Open
Election
Data
Project
Open
Data
Thesau-
rus
Ontos News Portal
OGOLOD
JanusAMP
Ocean Drilling Codices
New
York
Times
NVD
ntnusc
NTU
Resource
Lists
Norwe-
gian
MeSH
NDL subjects
ndlna
myExperi-ment
Italian
Museums
medu-
cator
MARC
Codes
List
Man-
chester
Reading
Lists
Lotico
Weather
Stations
London Gazette
LOIUS
Linked Open Colors
lobidResources
lobidOrgani-sations
LEM
LinkedMDB
LinkedLCCN
LinkedGeoData
LinkedCT
Linked
User
Feedback
LOV
Linked Open
Numbers
LODE
Eurostat (Ontology
Central)
Linked
EDGAR (Ontology
Central)
Linked
Crunch-
base
lingvoj
Lichfield
Spen-
ding
LIBRIS
Lexvo
LCSH
DBLP (L3S)
Linked Sensor Data (Kno.e.sis)
Klapp-
stuhl-
club
Good-
win
Family
National
Radio-
activity
JP
Jamendo
(DBtune)
Italian
public
schools
ISTAT Immi-gration
iServe
IdRef Sudoc
NSZL Catalog
Hellenic
PD
Hellenic FBD
Piedmont
Accomo-
dations
GovTrack
GovWILD
Art
wrapper
gnoss
GESIS
GeoWordNet
GeoSpecies
GeoNames
GeoLinkedData
GEMET
GTAA
STITCH
SIDER
Project
Guten-
berg
Medi
Care
Euro-
stat
(FUB)
EURES
DrugBank
Disea-
some
DBLP (FU
Berlin)
Daily
Med
CORDIS(FUB)
Freebase
flickr wrappr
Fishes of Texas
Finnish
Munici-
palities
ChEMBL
FanHubz
EventMedia
EUTC
Produc-
tions
Eurostat
Europeana
EUNIS
EU
Insti-
tutions
ESD
stan-
dards
EARTh
Enipedia
Popula-
tion (En-
AKTing)
NHS(En-
AKTing) Mortality
(En-
AKTing)
Energy
(En-
AKTing)
Crime
(En-
AKTing)
CO2
Emission
(En-
AKTing)
EEA
SISVU
education.data.g
ov.uk
ECS
South-
ampton
ECCO-
TCP
GND
Didactalia
DDC Deutsche
Bio-
graphie
data
dcs
MusicBrainz
(DBTune)
Magna-
tune
John
Peel (DBTune)
Classical
(DB
Tune)
AudioScrobbler (DBTune)
Last.FM artists
(DBTune)
DBTropes
Portu-guese
DBpedia
dbpedia lite
Greek DBpedia
DBpedia
data-open-ac-uk
SMC
Journals
Pokedex
Airports
NASA
(Data
Incu-
bator)
MusicBrainz(Data
Incubator)
Moseley
Folk
Metoffice Weather Forecasts
Discogs (Data
Incubator)
Climbing
data.gov.uk intervals
Data Gov.ie
databnf.fr
Cornetto
reegle
Chronic-ling
America
Chem2Bio2RDF
Calames
business
data.gov.
uk
Bricklink
Brazilian Poli-
ticians
BNB
UniSTS
UniPath
way
UniParc
Taxonomy
UniProt(Bio2RDF)
SGD
Reactome
PubMedPub
Chem
PRO-SITE
ProDom
Pfam
PDB
OMIMMGI
KEGG
Reaction
KEGG Pathway
KEGG
Glycan
KEGG Enzyme
KEGG
Drug
KEGG
Com-
pound
InterPro
HomoloGene
HGNC
Gene
Ontology
GeneID
Affy-metrix
bible
ontology
BibBase
FTS
BBC
Wildlife
Finder
BBC Program
mes BBC Music
Alpine
Ski
Austria
LOCAH
Amster-dam
Museum
AGROVOC
AEMET
US Census (rdfabout)
Media
Geographic
Publications
Government
Cross-domain
Life sciences
User-generated content
The Linked Open Data Cloud
Over 200 open data sets with more than 25 billion facts,
interlinked by 400 million typed links, doubling every 10 month!
see: http://lod-cloud.net/
Linking Open Data cloud diagram, by M. Schmachtenberg, C. Bizer, A. Jentzsch, Richard. Cyganiak
Media
Government
Geo
Publications
User-generated
Life sciences
Cross-domain
US government UK government
BBC New York Times
LinkedGeoData
BestBuy Overstock.com Facebook
Two Key Ingredients
1. RDF – Resource Description Framework Graph based Data – nodes and arcs
• Identifies objects (URIs)
• Interlink information (relationships)
2. Vocabularies (Ontologies)
• provide shared understanding of a domain
• organise knowledge in machine-comprehensible way
• give an exploitable meaning to the data
42
Cities:Dublin
84421km2
Geo:IslandOfIreland
EU:RepublicOfIreland
Geo:locatedOn
Geo:area
Geo:hasCapital
Geo:hasLargestCity
Wikipedia.org
Gov.ie
EU:RepublicOfIreland
Person:EndaKenny
Gov:hasTaoiseach
Gov:hasDepartment
IE:DepartmentOfFinance
Why Graphs and Ontologies?
43
Goal: Integrating IoT in LOD Cloud
44
http://www.flickr.com/photos/69730904@N03/8813574238/
Linked Data
Advantages of IoT Linked Data
IoT becomes part of the WWW
Open, independent standards and platforms
Global, established developer base
Extensible, open world
… but there is a problem
45
Linked Data and IoT
46
http://www.flickr.com/photos/69730904@N03/8813574238/
Linked Data
Challenges
47
‘classical LD’ IoT LD
Dynamism static, offline analysis Highly dynamic, online analysis
System resources
HPC, multicore CPUs, GBs RAM, TBs/PBs storage, fixed electrical
power grid connection
Embedded processors, kBs RAM, storage?, battery operated
Security and access control
manual, coarse grained access control
automated, fine grained access control
From Self-describing Data & Devices
Self-describing sensors (RDF)
Extended W3C SSN Ontology
Automatic discovery & integration
iSense nodes <http://www.example.org/s1> a ssn:Sensor;
ssn:onPlatform <http://www.example.org/
smartphone1>;
spt:obs ld4s:temperature;
spt:uom ld4s:centigrade;
corelf:bt "12-08-28T19:03Z";
spt:temporal ld4s:temporalprop3>;
spt:archive <http://www.example.org/
archive/historical_archive_a>.
ld4s:temporalprop3> a
spt:SensorTemporalProperty;
ssn:featureOfInterest ld4s:water;
dul:hasLocation ld4s:galway.
RDF storage
Semi-automatic annotation
with additional metadata
Self-sufficient sensor nodes
Central environment model
Export as standard
SPARQL end point
tim
e
sen
sors
en
viro
nm
en
t m
od
el
LOD
Clo
ud
…
To Self-describing Systems
To Semantic Event Streams
50
IoT Systems
LOD Cloud
Client
Client
...
Semantic Event
Processing
Contents
1. What is the Internet of Things
2. Connected Devices Perspective
3. Connected Data Perspective
4. Conclusion
51
What is the Internet of Things?
Imagine a World Were…
Every physical object is enhanced with a
computer
The Internet integrates all these computers
– wherever they are
Computers detect their physical surroundings
– including their users
… 52
What is the Internet of Things?
…
All this data is integrated, analysed and made
available globally – in (near) real-time
Results are send back to control / adapt the
physical world
The world becomes observable and
programmable in real-time 53
What will Become Possible?
Never forgetting anything you see or hear – forever?
Knowing what someone feels?
Knowing who has touched an object you have just acquired?
Changing your environment by waving a hand or thinking?
Detecting and influencing thinking?
Predicting the future?
…
54
Questions
55
ES
I Y
NS
GTE
EB
ME
ET T E T E
der Informatik
Bismarckstr. 90 Gebäude BC 1. Etage 47057 Duisburg https://www.uni-due.de/es/ [email protected] Tel: +49 203 379 3620
Linked Data