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THE IOT CORE –INDUSTRIAL EDGE INTELLIGENCE PLATFORM
MESERP
PLM
Orc
hes
trat
ion
Cloud Global Analytics IoT Platform
Wide Area
EdgeEdge Analytics,Device Managementand Controllers
Edge Node Enterprise
Fog Local Analyticsand Controllers Fog Node
Field/ Shop Floor
Fog to Fog Communication
Data Protection
LatencySecurity
Autonomy
The IoT Core enables a broad range of industr ia l IoT appl icat ions providing new levels of autonomy,
res i l ience, data secur i ty and l ightning fast analyt ics on-the-spot.
FOG/ EDGE REAL-TIME ANALYTICS AND MACHINE LEARNING
Among several other advantages, fog-computing allows for
significant network capacity optimization, as less bandwidth is
utilized on shop-floor-, enterprise-network and internet
uplinks, significantly reducing bottlenecks and enabling fewer
network congestions.
Depending on the number of networked sensor devices and
controlled actuators, the frequency and format of data
exchanged (sensor on video data) and on the complexity of
analytic computations, the IoT Core can be deployed on
embedded mini-computers, industrial gateways and edge
nodes, micro-datacenters as well as Cloud backends.
As topologies and heterogeneity of distributed fog-/ edge-/
cloud-computing infrastructures can vary considerably, in
many cases intelligent application orchestration systems are
required, capable of dynamically deploying, managing and
elastically scaling the compute infrastructure.
Despite its broadly recognized power, the applicability of
Cloud Computing for time-critical operations is highly limited.
Especially in manufacturing, automotive or telemedicine
scenarios, where latencies caused by the roundtrip to cloud
servers can have fatal consequences. Real-time intelligence at
the fog/edge level is required.
Fog/ Edge intelligence also provides new levels of resilience
and autonomy, as poor connectivity or network outages do
not affect local, mission-critical control loops. Wireless
Fog-to-Fog communication mechanisms allow for autonomous
device-to-device communication which, unlike cloud-based
communication still functions during network performance
degradation.
By aggregating and analyzing data locally fog/edge-based data
processing yields several data-security related advantages
compared to traditional cloud-computing mechanisms. Not
only can communication and exposition of sensitive data to
external data centers be fully omitted, but also finely config-
ured, which data is being sent to external parties, how data is
being filtered, anonymized and encrypted and how the
communication channels between local and external infra-
structures are being secured.
Benefits of Fog-/ Edge Intelligence
MISSION-CRITICAL INTELLIGENCE ON-THE-SPOT
Combining fog-/ edge-/ cloud computing mechanisms with
advanced real-time stream analytics and machine learning
techniques enables a broad range of mission-critical industrial
IoT applications. By providing advanced M2M connectivity
through latest low-power wide area networks (LPWAN) and
deterministic time-sensitive networking (TSN) technologies,
edge intelligence is brought to smart cities in just the same
way as to Industry 4.0 environments.
Industrial IoT Standards, M2M Protocols and APIs (OPC UA,
OneM2M) are provided to assure seamless integration and
interoperability. Time-Critical Stream Analytics is enabled by
latest Complex Event Processing (CEP), Machine Learning and
Video Analytics modules, deployed on COTS fog-/ edge- as
well as cloud-hardware infrastructures. Stream analytics
algorithms (CEP, classification and regression models, decision
trees, clustering, statistical analysis), as well as video analytics
Offerings:
– IoT Core Solution: Hardware selection,
Deployment, Integration and Licensing
– IoT Testbeds: Feasibility-, Stress- Safety-,
Security-Testing and Quality Assurance
– CPS-Enablement and Retrofitting: Mounting and
interconnecting industrial sensors, drives and
controllers with subsequent real-time data
aggregation and controller logic programming
– Predictive Analytics & Artificial Intelligence:
Modelling, Calibration and Application of
advanced AI and Machine Learning Techniques
for condition monitoring, predictive maintenance
and safety applications
– IoT and Data Analytics Training, Consultation &
Knowledge Transfer
Goals and Focal Points:
– Demonstration, implementation and testing of
IoT Technologies & Applications
– Versatile infrastructure enabling rapid
implementation of IoT projects with industry
partners and academia
Key Application Domains and Customers:
– Industrial IoT: Shop-floor owners, operators and
vendors of manufacturing and logistics equipment
– Public IoT: Smart Cities, eHealth, ministries and
IT service providers
W I T H A D V A N C E D D A T A A N A L Y T I C S
A N D M A C H I N E L E A R N I N G T E C H N I Q U E S
T H E I O T C O R E E N A B L E S
A R T I F I C I A L I N T E L L I G E N C E A T T H E E D G E
Ap
pli
cati
on
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etw
ork
&C
on
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evic
esIn
fras
tru
ctu
res
& P
latf
orm
s DeviceManagement
TSN
iWireless
DataManagement
M2MCommunication
Management &Orchestration
StramProcessing
VideoAnalytics
MachineLearning
Fog & EdgeComputing
LoRa
NB-IoT
Condition Monitoring
PredictiveMaintainance Safety Retrofitting
Smart City
PLC
Industry 4.0
CPS/ Gateway
SDN/ NFV
functions (object, motion detection, tracking, counting &
diagnosis, 3D video analysis) enable a broad range of use
cases. The IoT Core is provided as a module of the OpenIoT-
Fog Industry 4.0 toolkit on www.openiotfog.org.
Contact us for an IoT Core live demonstration or join us
at one of our upcoming events to learn more about the
IoT Core and our services: [email protected]!
“The next multi-billion-dollar tech market was quietly born this year.A large portion of computation that gets done in the cloud today will return to the edge.”
Peter Levine,
General Partner at Andreessen Horowitz, 2016
EDGE INTELLIGENCE USE CASES
With edge intelligence a plethora of use cases from automo-
tive to smart manufacturing, telehealth and smart city safety
are enabled. The following few example applications realized
within the Transfer Center IoT show the power of fog-/
edge-based data processing and local actuation.
Edge Intelligence enables Public Safety & Privacy
Through intelligent, distributed, autonomous Fog-based
(video) data analysis and public surveillance systems are
enabled to autonomously analyze public surveillance video
data and trigger safety and defense actions without violating
data protection and privacy regulations. Thereby an entirely
new generation of public surveillance and safety services can
readily be rolled out. By enforcing strict video data protection
rules at the fog/edge level, the overall system complies with
German privacy regulations. Through Fog-to-Fog communica-
tion mechanisms ultra-low latency levels are achieved. Highest
levels of autonomy, resilience and robustness are achieved by
local data processing and local actuator control.
Edge Intelligence enables Industry 4.0
“Retrofitting” Industry 3.0 Shop Floor Assets allows for the
monitoring of equipment performance and factory processes
thus enabling the “digital twin”. Combined with hard
real-time networking (TSN), hard & soft PLC interworking and
fast stream analytics the IoT Core provides cost-effective
means for monitoring and increasing Overall Equipment
Effectiveness (OEE), enables Condition Monitoring & Predictive
Maintenance as well as industrial Safety applications. Factory
integration involves
– Deployment of IIoT Core Gateways in the field,
– monitoring and control through OPC UA based PLCs,
– Mounting of e.g. Micro-Electro-Mechanical Systems
(MEMS) and many other sensors for aggregation of missing
asset/ equipment data
– Local, real-time data analytics for rapid and direct asset
control (safety, hazards, etc.) exploiting Machine Learning
techniques
Retrofitting
StramProcessing
VideoAnalytics
MachineLearning
Fog & EdgeComputing
Condition Monitoring
PredictiveMaintainance Safety Retrofitting
PLC
Industrial Devices, Sensors, PLC‘s
CPS/ Gateway
Integration
GlobalAnalytics
LocalAnalytics
Global Cloud
Smart City
Data Protection& Filtering
Fog Node Fog Node Fog Node
Fog to Fog Communication
Fog to Cloud Communication
Cloud to Fog Communication
Analyzed Dataw/o security
relevanceSensor Actuator
T H E C O S T E F F E C T I V E I O T C O R E P R O V I D E S
U N P R E C E D E N T E D L E V E L S O F A U T O M A T I O N ,
O P E R A T I O N A L E F F I C I E N C Y A N D
C O S T S A V I N G S F O R I N D U S T R I A L I O T
Fog-/ Edge Intelligence for public surveillance Fog-/ Edge Intelligence for Retrofitting and Condition Monitoring
supported by:
EUROPEAN UNIONEuropean Regional Development Fund
CONTACT
Prof. Dr. rer. nat Adrian Paschke
Head of Data Analytics Center
Phone +49 30 3463-7228
Fax +49 30 3463-99 7228
Dr.-Ing. Alexander Willner
Head of IIoT Center
Phone +49 30 3463- 7116
Fax +49 30 3463-99 7116
Dr.-Ing. Florian Schreiner
Head of Transfer Center IoT
Phone +49 30 3463-7174
Fax +49 30 3463-99 7174
Fraunhofer FOKUS Kaiserin-Augusta-Allee 31
10589 Berlin Germany
www.openiotfog.org
www.iiot-center.org
www.data-analytics-center.org
www.digitale-vernetzung.org
www.internet-of-things-lab.org
mfr | 1710 (Photos: Phonlamai Photo/ shutterstock;
Zapp2Photo/ shutterstock; Fraunhofer FOKUS)
