by r. nabati rnabati@gmail.com iausdj.ac.ir Dr. Abdulbaghi Ghaderzadeh

1. Smart Manufacturing
Through Cloud-Based
Smart Objects and SWE
An Article by: Pablo Giménez, Benjamín Molina, Carlos E. Palau, Manuel
Esteve and Jaime Calvo, 2014.
CE Dep, IAUSDJ.ac.ir
21-02-96(1 April, 2017)
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2. 2

3. Introduction
Motivation and Previous Work
Outline of the System
Design and Development
Use Case
Conclusions and Future Work
References
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4. 4

5.  Security technological advances in Industrial
environments.
 but there are still risks concerning worker’s
safety and health.
 Therefore new integrated approaches to
ensure the continuous safety and wellness of
workers
 we propose the usage of smart virtualized
objects to perform intelligent tasks such as
increasing productivity and minimizing risks 5

6. The IoT evolving from:
Simple sensors with network connectivity
Smart Objects (SO): Interrelated and
interconnected objects.
SOs are fully functional on their own.
Proposed system perceived as aWSN.
WSN enable applications to obtain up-to-date
information about the physical world.
6LowPAN (IPv6 over low power mesh network).
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7. 7

8.  Smart Objects provide a set of new resources
to be consumed by networks, services and
applications.
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9.  The SWE architecture component that has
been used and analysed in this document is
the SOS.
 The main purpose of this service consists in
allowing access to sensor observations in a
standard way for any sensor system.
 SOS+O&M=modeling sensor observations,
 SOS+SensorML modelling=sensors and
sensor systems.
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10.  A unique identification
 Capability to communicate effectively with its
environment
 Data storage about itself
 A language to display its features and its needs over its
lifecycle
 Capability to participate in or making individual
decisions relevant to its own destiny
 Capability for surveying and controlling its environment
 Generation of interaction by services offering:
contextual, personal and reactive services
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11.  Considering sensors (and evenWSNs) as
small systems with limited (processing)
capabilities
 It makes sense to virtualize its capabilities in a
data centre
 so that sensors (WSNs) perceive that they are
as powerful as normal computers.
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12.  OGC, Open Geospatial Consortium
 SWE, SensorWeb Enablement
 The OGC's SensorWeb Enablement (SWE)
standards enable developers to make all
types of sensors, transducers and sensor data
repositories discoverable, accessible and
useable via theWeb.
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13. 13

14.  The information model describes the
conceptual models
 Refer to transducers, processes, systems and observations.
such as: (i)Transducer Markup Language (TML), currently
deprecated; (ii) Sensor Model Language (SensorML); (iii)
Observation and Measurements (O&M).
 The service model specifies related services.
 Refer to (i) Sensor Alert Service (SAS); (ii) Sensor Planning
Services (SPS); (iii)Web Notification Service (WNS); (iv)
Catalog ServiceWeb (CSW); and (v) Sensor Observation
Service (SOS).
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17. 17

18. 18

19. 19

20. 20

21.  European Factories of the Future (FoF)
focuses on the development and integration
of engineering technologies, Information and
CommunicationTechnology (ICT), and
advanced materials for adaptable machines
and industrial processes
 workers represent an even more important
asset.
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22.  The proposed use case belongs to a Spanish
FoF project named FASyS
 The project was related with the
development of a large wireless sensor
system in order to provide safety to the
workers.
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23. 23

24.  Thus our system has to alert both drivers only when
both lift trucks have crossed their red (risk) lines
 The Control Center (CC) must keep track of the
position of each lift truck
 It inserts its position in the SOS everyTa seconds
 The control center reads from the SOS everyTread
seconds Alerting both vehicles takes some time
(Tsend) and an acknowledgment (Tack) from each
vehicle
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25.  Experimental Results:
 mean time (Tsend +Tack) is 200 ms
 variability of 50 ms
 If the CC performs correctly (successfully), the
driver is alerted Δx meters before crossing
the risk line
 To avoid alerting drivers a and b too late,
there is a safety distance (xS and yS).
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27. 27

28. 28

29. 29

30. 30

31.  The presented system is able to avoid
collisions between automatic machineries or
lift trucks in a factory.
 To achieve this goal several components are
needed:WSN, SOS, CEP, HMI, A Cloud
computing environment
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32.  The CEP is physically in a single computer
 SO’s is the smart objects are distributed
 we can qualitatively estimate that the final
time is slightly higher
 The processing time in the SO is significantly
low compared to a CEP.
 The SO only cares for a single vehicle
whereas the CEP (test case 1) cares for the
whole factory
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33.  However the CEP does not require a NC as it
interacts directly with theWSNs; the SOs, on
the contrary, require the NC to exchange
notifications
 CEP can query the SOS to retrieve more
information on a single message whereas
each SO requires single (and simpler)
messages.
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34.  As the SOs are independent objects, the
system is decentralized, so if one of them
goes down it does not imply the failure of the
whole system.
 The use of cloud computing (self-healing)
mechanisms also helps in detecting failures
and recovering immediately.
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38. Only the death
have seen
the end of war
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39. Thank you for
your attention.
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