Smart manufacturing through cloud based-r-nabati--dr abdulbaghi ghaderzadeh
- 1. Smart Manufacturing Through Cloud-Based Smart Objects and SWE An Article by: Pablo GimΓ©nez, BenjamΓn Molina, Carlos E. Palau, Manuel Esteve and Jaime Calvo, 2014. CE Dep, IAUSDJ.ac.ir 21-02-96(1 April, 2017) 1
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- 3. Introduction Motivation and Previous Work Outline of the System Design and Development Use Case Conclusions and Future Work References 3
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- 5. ο‘ Security technological advances in Industrial environments. ο‘ but there are still risks concerning workerβs safety and health. ο‘ Therefore new integrated approaches to ensure the continuous safety and wellness of workers ο‘ 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: ο‘Simple sensors with network connectivity ο‘Smart Objects (SO): Interrelated and interconnected objects. ο‘SOs are fully functional on their own. ο‘Proposed system perceived as aWSN. ο‘WSN enable applications to obtain up-to-date information about the physical world. ο‘6LowPAN (IPv6 over low power mesh network). 6
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- 8. ο‘ Smart Objects provide a set of new resources to be consumed by networks, services and applications. 8
- 9. ο‘ The SWE architecture component that has been used and analysed in this document is the SOS. ο‘ The main purpose of this service consists in allowing access to sensor observations in a standard way for any sensor system. ο‘ SOS+O&M=modeling sensor observations, ο‘ SOS+SensorML modelling=sensors and sensor systems. 9
- 10. ο‘ A unique identification ο‘ Capability to communicate effectively with its environment ο‘ Data storage about itself ο‘ A language to display its features and its needs over its lifecycle ο‘ Capability to participate in or making individual decisions relevant to its own destiny ο‘ Capability for surveying and controlling its environment ο‘ Generation of interaction by services offering: contextual, personal and reactive services 10
- 11. ο‘ Considering sensors (and evenWSNs) as small systems with limited (processing) capabilities ο‘ It makes sense to virtualize its capabilities in a data centre ο‘ so that sensors (WSNs) perceive that they are as powerful as normal computers. 11
- 12. ο‘ OGC, Open Geospatial Consortium ο‘ SWE, SensorWeb Enablement ο‘ 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. 12
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- 14. ο‘ The information model describes the conceptual models ο§ 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). ο‘ The service model specifies related services. ο§ 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). 14
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- 21. ο‘ 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 ο‘ workers represent an even more important asset. 21
- 22. ο‘ The proposed use case belongs to a Spanish FoF project named FASyS ο‘ The project was related with the development of a large wireless sensor system in order to provide safety to the workers. 22
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- 24. ο‘ Thus our system has to alert both drivers only when both lift trucks have crossed their red (risk) lines ο‘ The Control Center (CC) must keep track of the position of each lift truck ο‘ It inserts its position in the SOS everyTa seconds ο‘ The control center reads from the SOS everyTread seconds Alerting both vehicles takes some time (Tsend) and an acknowledgment (Tack) from each vehicle 24
- 25. ο‘ Experimental Results: ο§ mean time (Tsend +Tack) is 200 ms ο§ variability of 50 ms ο‘ If the CC performs correctly (successfully), the driver is alerted Ξx meters before crossing the risk line ο‘ To avoid alerting drivers a and b too late, there is a safety distance (xS and yS). 25
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- 31. ο‘ The presented system is able to avoid collisions between automatic machineries or lift trucks in a factory. ο‘ To achieve this goal several components are needed:WSN, SOS, CEP, HMI, A Cloud computing environment 31
- 32. ο‘ The CEP is physically in a single computer ο‘ SOβs is the smart objects are distributed ο‘ we can qualitatively estimate that the final time is slightly higher ο‘ The processing time in the SO is significantly low compared to a CEP. ο‘ The SO only cares for a single vehicle whereas the CEP (test case 1) cares for the whole factory 32
- 33. ο‘ 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 ο‘ CEP can query the SOS to retrieve more information on a single message whereas each SO requires single (and simpler) messages. 33
- 34. ο‘ 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. ο‘ The use of cloud computing (self-healing) mechanisms also helps in detecting failures and recovering immediately. 34
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- 39. Thank you for your attention. 39
Editor's Notes
- #17: Notification Center (NC) module Common Resource Repository (CRR)=environmental facilities Personal Data Record (PDR)
- #18: Sensor Model Language (SensorML); (iii) Observation and Measurements (O&M).
- #24: CEP, Complex Event Processing
- #25: CEP, Complex Event Processing
- #26: CEP, Complex Event Processing
- #31: RC= Risk of Collision NC=Notification Center