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Cyber-physical system

February 18, 2023

A cyber-physical system (CPS) or intelligent system is a computer system in which a mechanism is controlled or monitored by computer-based algorithms. In cyber-physical systems, physical and software components are deeply intertwined, able to operate on different spatial and temporal scales, exhibit multiple and distinct behavioral modalities, and interact with each other in ways that change with context.[1][2] CPS involves transdisciplinary approaches, merging theory of cybernetics, mechatronics, design and process science.[3][4][5] The process control is often referred to as embedded systems. In embedded systems, the emphasis tends to be more on the computational elements, and less on an intense link between the computational and physical elements. CPS is also similar to the Internet of Things (IoT), sharing the same basic architecture; nevertheless, CPS presents a higher combination and coordination between physical and computational elements.[6]

Examples of CPS include smart grid, autonomous automobile systems, medical monitoring, industrial control systems, robotics systems, and automatic pilot avionics.[2][7] Precursors of cyber-physical systems can be found in areas as diverse as aerospace, automotive, chemical processes, civil infrastructure, energy, healthcare, manufacturing, transportation, entertainment, and consumer appliances.[7]

Overview

Unlike more traditional embedded systems, a full-fledged CPS is typically designed as a network of interacting elements with physical input and output instead of as standalone devices.[3] The notion is closely tied to concepts of robotics and sensor networks with intelligence mechanisms proper of computational intelligence leading the pathway. Ongoing advances in science and engineering improve the link between computational and physical elements by means of intelligent mechanisms, increasing the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems.[8] This will broaden the potential of cyber-physical systems in several directions, including: intervention (e.g., collision avoidance); precision (e.g., robotic surgery and nano-level manufacturing); operation in dangerous or inaccessible environments (e.g., search and rescue, firefighting, and deep-sea exploration); coordination (e.g., air traffic control, war fighting); efficiency (e.g., zero-net energy buildings); and augmentation of human capabilities (e.g. in healthcare monitoring and delivery).[9]

Mobile cyber-physical systems

Mobile cyber-physical systems, in which the physical system under study has inherent mobility, are a prominent subcategory of cyber-physical systems. Examples of mobile physical systems include mobile robotics and electronics transported by humans or animals. The rise in popularity of smartphones has increased interest in the area of mobile cyber-physical systems. Smartphone platforms make ideal mobile cyber-physical systems for a number of reasons, including:

For tasks that require more resources than are locally available, one common mechanism for rapid implementation of smartphone-based mobile cyber-physical system nodes utilizes the network connectivity to link the mobile system with either a server or a cloud environment, enabling complex processing tasks that are impossible under local resource constraints.[11] Examples of mobile cyber-physical systems include applications to track and analyze CO2 emissions,[12] detect traffic accidents, insurance telematics[13] and provide situational awareness services to first responders,[14][15] measure traffic,[16] and monitor cardiac patients.[17]

Examples

Common applications of CPS typically fall under sensor-based communication-enabled autonomous systems. For example, many wireless sensor networks monitor some aspect of the environment and relay the processed information to a central node. Other types of CPS include smart grid,[18] autonomous automotive systems, medical monitoring, process control systems, distributed robotics, and automatic pilot avionics.

A real-world example of such a system is the Distributed Robot Garden at MIT in which a team of robots tend a garden of tomato plants. This system combines distributed sensing (each plant is equipped with a sensor node monitoring its status), navigation, manipulation and wireless networking.[19]

A focus on the control system aspects of CPS that pervade critical infrastructure can be found in the efforts of the Idaho National Laboratory and collaborators researching resilient control systems. This effort takes a holistic approach to next generation design, and considers the resilience aspects that are not well quantified, such as cyber security,[20] human interaction and complex interdependencies.

Another example is MIT's ongoing CarTel project where a fleet of taxis work by collecting real-time traffic information in the Boston area. Together with historical data, this information is then used for calculating fastest routes for a given time of the day.[21]

CPS are also used in electric grids to perform advanced control, especially in the smart grids context to enhance the integration of distributed renewable generation. Special remedial action scheme are needed to limit the current flows in the grid when wind farm generation is too high. Distributed CPS are a key solution for this type of issues [22]

In industry domain, the cyber-physical systems empowered by Cloud technologies have led to novel approaches[23][24][25] that paved the path to Industry 4.0 as the European Commission IMC-AESOP project with partners such as Schneider Electric, SAP, Honeywell, Microsoft etc. demonstrated.

Design

 

A challenge in the development of embedded and cyber-physical systems is the large differences in the design practice between the various engineering disciplines involved, such as software and mechanical engineering. Additionally, as of today there is no "language" in terms of design practice that is common to all the involved disciplines in CPS. Today, in a marketplace where rapid innovation is assumed to be essential, engineers from all disciplines need to be able to explore system designs collaboratively, allocating responsibilities to software and physical elements, and analyzing trade-offs between them. Recent advances show that coupling disciplines by using co-simulation will allow disciplines to cooperate without enforcing new tools or design methods.[26] Results from the MODELISAR project show that this approach is viable by proposing a new standard for co-simulation in the form of the Functional Mock-up Interface.

Importance

The US National Science Foundation (NSF) has identified cyber-physical systems as a key area of research.[27] Starting in late 2006, the NSF and other United States federal agencies sponsored several workshops on cyber-physical systems.[28][29][30][31][32][33][34][35][36]

See also

References

  1. ^ "US National Science Foundation, Cyber-Physical Systems (CPS)"
  2. ^ a b Hu, J.; Lennox, B.; Arvin, F., "Robust formation control for networked robotic systems using Negative Imaginary dynamics" Automatica, 2022.
  3. ^ a b Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F., "Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring" Aerospace Science and Technology, 2022.
  4. ^ Hancu, O.; Maties, V.; Balan, R.; Stan, S. (2007). "Mechatronic approach for design and control of a hydraulic 3-dof parallel robot". The 18th International DAAAM Symposium, "Intelligent Manufacturing & Automation: Focus on Creativity, Responsibility and Ethics of Engineers".
  5. ^ Suh, S.C., Carbone, J.N., Eroglu, A.E.: Applied Cyber-Physical Systems. Springer, 2014.
  6. ^ Rad, Ciprian-Radu; Hancu, Olimpiu; Takacs, Ioana-Alexandra; Olteanu, Gheorghe (2015). "Smart Monitoring of Potato Crop: A Cyber-Physical System Architecture Model in the Field of Precision Agriculture". Conference Agriculture for Life, Life for Agriculture. 6: 73–79.
  7. ^ a b Khaitan et al., "Design Techniques and Applications of Cyber Physical Systems: A Survey", IEEE Systems Journal, 2014.
  8. ^ C.Alippi: Intelligence for Embedded Systems. Springer Verlag, 2014, 283pp, ISBN 978-3-319-05278-6.
  9. ^ "Cyber-physical systems". Program Announcements & Information. The National Science Foundation, 4201 Wilson Boulevard, Arlington, Virginia 22230, USA. 2008-09-30. Retrieved 2009-07-21.
  10. ^ "Virtual Machine for running Java Applications on a CPS". Retrieved 2012-04-12.
  11. ^ White, Jules; Clarke, S.; Dougherty, B.; Thompson, C.; Schmidt, D. (PDF). Springer Journal of Internet Services and Applications. Archived from the original (PDF) on 2016-08-04. Retrieved 2011-02-21.
  12. ^ J. Froehlich, T. Dillahunt, P. Klasnja, J. Mankoff, S. Consolvo, B. Harrison, and J. Landay, "UbiGreen: investigating a mobile tool for tracking and supporting green transportation habits," in Proceedings of the 27th international conference on Human factors in computing systems. ACM, 2009, pp. 1043–1052.
  13. ^ P. Handel, I. Skog, J. Wahlstrom, F. Bonawide, R. Welsh, J. Ohlsson, and M. Ohlsson: Insurance telematics: opportunities and challenges with the smartphone solution, Intelligent Transportation Systems Magazine, IEEE, vol.6, no.4, pp. 57-70, winter 2014, doi:10.1109/MITS.2014.2343262
  14. ^ Thompson, C.; White, J.; Dougherty, B.; Schmidt, D. C. (2009). "Optimizing Mobile Application Performance with Model–Driven Engineering" (PDF). Software Technologies for Embedded and Ubiquitous Systems. Lecture Notes in Computer Science. Vol. 5860. p. 36. doi:10.1007/978-3-642-10265-3_4. ISBN 978-3-642-10264-6.
  15. ^ Jones, W. D. (2001). "Forecasting traffic flow". IEEE Spectrum. 38: 90–91. doi:10.1109/6.901153.
  16. ^ Rose, G. (2006). "Mobile Phones as Traffic Probes: Practices, Prospects and Issues". Transport Reviews. 26 (3): 275–291. doi:10.1080/01441640500361108. S2CID 109790299.
  17. ^ Leijdekkers, P. (2006). "Personal Heart Monitoring and Rehabilitation System using Smart Phones". 2006 International Conference on Mobile Business. p. 29. doi:10.1109/ICMB.2006.39. hdl:10453/2740. ISBN 0-7695-2595-4. S2CID 14750674.
  18. ^ S. Karnouskos: Cyber-Physical Systems in the Smart Grid (PDF; 79 kB). In:Industrial Informatics (INDIN), 2011 9th IEEE International Conference on, July 2011. Retrieved 20 Apr 2014.
  19. ^ "The Distributed Robotics Garden". people.csail.mit.edu. 2011. Retrieved November 16, 2011.
  20. ^ Loukas, George (June 2015). Cyber-Physical Attacks A growing invisible threat. Oxford, UK: Butterworh-Heinemann (Elsevier). p. 65. ISBN 9780128012901.
  21. ^ . cartel.csail.mit.edu. 2011. Archived from the original on August 11, 2007. Retrieved November 16, 2011.
  22. ^ Liu, R.; Srivastava, A. K.; Bakken, D. E.; Askerman, A.; Panciatici, P. (November–December 2017). "Decentralized State Estimation and Remedial Control Action for Minimum Wind Curtailment Using Distributed Computing Platform". IEEE Transactions on Industry Applications. 53 (6): 5915. doi:10.1109/TIA.2017.2740831. OSTI 1417238.
  23. ^ A. W. Colombo, T. Bangemann, S. Karnouskos, J. Delsing, P. Stluka, R. Harrison, F. Jammes, and J. Lastra: Industrial Cloud-based Cyber- Physical Systems: The IMC-AESOP Approach. Springer Verlag, 2014, ISBN 978-3-319-05623-4.
  24. ^ Wu, D.; Rosen, D.W.; Wang, L.; Schaefer, D. (2014). "Cloud-Based Design and Manufacturing: A New Paradigm in Digital Manufacturing and Design Innovation" (PDF). Computer-Aided Design. 59: 1–14. doi:10.1016/j.cad.2014.07.006. S2CID 9315605.
  25. ^ Wu, D., Rosen, D.W., & Schaefer, D. (2014). Cloud-Based Design and Manufacturing: Status and Promise. In: Schaefer, D. (Ed): Cloud-Based Design and Manufacturing: A Service-Oriented Product Development Paradigm for the 21st Century, Springer, London, UK, pp.1-24.
  26. ^ J .Fitzgerald, P.G. Larsen, M. Verhoef (Eds.): Collaborative Design for Embedded Systems: Co-modelling and Co-simulation. Springer Verlag, 2014, ISBN 978-3-642-54118-6.
  27. ^ Wolf, Wayne (November 2007). "The Good News and the Bad News (Embedded Computing Column". IEEE Computer. 40 (11): 104–105. doi:10.1109/MC.2007.404.
  28. ^ . Archived from the original on 2008-05-17. Retrieved 2008-06-09.
  29. ^ . Archived from the original on January 17, 2009. Retrieved 2008-06-09.
  30. ^ . Archived from the original on 2009-05-12. Retrieved 2008-08-01.
  31. ^ . Archived from the original on 2008-08-27. Retrieved 2008-08-03.
  32. ^ "National Workshop on Composable and Systems Technologies for High-Confidence Cyber-Physical Systems". Retrieved 2008-08-04.
  33. ^ "National Workshop on High-Confidence Software Platforms for Cyber-Physical Systems (HCSP-CPS)". Retrieved 2008-08-04.
  34. ^ "New Research Directions for Future Cyber-Physical Energy Systems". Retrieved 2009-06-05.
  35. ^ "Bridging the Cyber, Physical, and Social Worlds". Archived from the original on 2012-07-16. Retrieved 2011-02-25.
  36. ^ . Archived from the original on 2015-08-20. Retrieved 2012-02-08.

Further reading

  • Edward A. Lee, Cyber-Physical Systems - Are Computing Foundations Adequate?
  • Paulo Tabuada,
  • Rajesh Gupta,
  • E. A. Lee and S. A. Seshia, Introduction to Embedded Systems - A Cyber-Physical Systems Approach, http://LeeSeshia.org, 2011.
  • Altawy R., Youssef A., Security Trade-offs in Cyber Physical Systems: A Case Study Survey on Implantable Medical Devices
  • Ahmad I., Security Aspects of Cyber Physical Systems

External links

  • The CPS Virtual Organization
  • Cyber-Physical Systems Week conference Illustrates current research in the area
  • Transactions on Cyber-Physical Systems ACM Journal in this area

February 18, 2023
cyber, physical, system, cyber, physical, system, intelligent, system, computer, system, which, mechanism, controlled, monitored, computer, based, algorithms, cyber, physical, systems, physical, software, components, deeply, intertwined, able, operate, differe. A cyber physical system CPS or intelligent system is a computer system in which a mechanism is controlled or monitored by computer based algorithms In cyber physical systems physical and software components are deeply intertwined able to operate on different spatial and temporal scales exhibit multiple and distinct behavioral modalities and interact with each other in ways that change with context 1 2 CPS involves transdisciplinary approaches merging theory of cybernetics mechatronics design and process science 3 4 5 The process control is often referred to as embedded systems In embedded systems the emphasis tends to be more on the computational elements and less on an intense link between the computational and physical elements CPS is also similar to the Internet of Things IoT sharing the same basic architecture nevertheless CPS presents a higher combination and coordination between physical and computational elements 6 Examples of CPS include smart grid autonomous automobile systems medical monitoring industrial control systems robotics systems and automatic pilot avionics 2 7 Precursors of cyber physical systems can be found in areas as diverse as aerospace automotive chemical processes civil infrastructure energy healthcare manufacturing transportation entertainment and consumer appliances 7 Contents 1 Overview 2 Mobile cyber physical systems 3 Examples 4 Design 5 Importance 6 See also 7 References 8 Further reading 9 External linksOverview EditUnlike more traditional embedded systems a full fledged CPS is typically designed as a network of interacting elements with physical input and output instead of as standalone devices 3 The notion is closely tied to concepts of robotics and sensor networks with intelligence mechanisms proper of computational intelligence leading the pathway Ongoing advances in science and engineering improve the link between computational and physical elements by means of intelligent mechanisms increasing the adaptability autonomy efficiency functionality reliability safety and usability of cyber physical systems 8 This will broaden the potential of cyber physical systems in several directions including intervention e g collision avoidance precision e g robotic surgery and nano level manufacturing operation in dangerous or inaccessible environments e g search and rescue firefighting and deep sea exploration coordination e g air traffic control war fighting efficiency e g zero net energy buildings and augmentation of human capabilities e g in healthcare monitoring and delivery 9 Mobile cyber physical systems EditMobile cyber physical systems in which the physical system under study has inherent mobility are a prominent subcategory of cyber physical systems Examples of mobile physical systems include mobile robotics and electronics transported by humans or animals The rise in popularity of smartphones has increased interest in the area of mobile cyber physical systems Smartphone platforms make ideal mobile cyber physical systems for a number of reasons including Significant computational resources such as processing capability local storage Multiple sensory input output devices such as touch screens cameras GPS chips speakers microphone light sensors proximity sensors Multiple communication mechanisms such as WiFi 4G EDGE Bluetooth for interconnecting devices to either the Internet or to other devices High level programming languages that enable rapid development of mobile CPS node software such as Java 10 C or JavaScript Readily available application distribution mechanisms such as Google Play Store and Apple App Store End user maintenance and upkeep including frequent re charging of the batteryFor tasks that require more resources than are locally available one common mechanism for rapid implementation of smartphone based mobile cyber physical system nodes utilizes the network connectivity to link the mobile system with either a server or a cloud environment enabling complex processing tasks that are impossible under local resource constraints 11 Examples of mobile cyber physical systems include applications to track and analyze CO2 emissions 12 detect traffic accidents insurance telematics 13 and provide situational awareness services to first responders 14 15 measure traffic 16 and monitor cardiac patients 17 Examples EditCommon applications of CPS typically fall under sensor based communication enabled autonomous systems For example many wireless sensor networks monitor some aspect of the environment and relay the processed information to a central node Other types of CPS include smart grid 18 autonomous automotive systems medical monitoring process control systems distributed robotics and automatic pilot avionics A real world example of such a system is the Distributed Robot Garden at MIT in which a team of robots tend a garden of tomato plants This system combines distributed sensing each plant is equipped with a sensor node monitoring its status navigation manipulation and wireless networking 19 A focus on the control system aspects of CPS that pervade critical infrastructure can be found in the efforts of the Idaho National Laboratory and collaborators researching resilient control systems This effort takes a holistic approach to next generation design and considers the resilience aspects that are not well quantified such as cyber security 20 human interaction and complex interdependencies Another example is MIT s ongoing CarTel project where a fleet of taxis work by collecting real time traffic information in the Boston area Together with historical data this information is then used for calculating fastest routes for a given time of the day 21 CPS are also used in electric grids to perform advanced control especially in the smart grids context to enhance the integration of distributed renewable generation Special remedial action scheme are needed to limit the current flows in the grid when wind farm generation is too high Distributed CPS are a key solution for this type of issues 22 In industry domain the cyber physical systems empowered by Cloud technologies have led to novel approaches 23 24 25 that paved the path to Industry 4 0 as the European Commission IMC AESOP project with partners such as Schneider Electric SAP Honeywell Microsoft etc demonstrated Design Edit A challenge in the development of embedded and cyber physical systems is the large differences in the design practice between the various engineering disciplines involved such as software and mechanical engineering Additionally as of today there is no language in terms of design practice that is common to all the involved disciplines in CPS Today in a marketplace where rapid innovation is assumed to be essential engineers from all disciplines need to be able to explore system designs collaboratively allocating responsibilities to software and physical elements and analyzing trade offs between them Recent advances show that coupling disciplines by using co simulation will allow disciplines to cooperate without enforcing new tools or design methods 26 Results from the MODELISAR project show that this approach is viable by proposing a new standard for co simulation in the form of the Functional Mock up Interface Importance EditThe US National Science Foundation NSF has identified cyber physical systems as a key area of research 27 Starting in late 2006 the NSF and other United States federal agencies sponsored several workshops on cyber physical systems 28 29 30 31 32 33 34 35 36 See also EditDigital twin Indoor positioning system Industry 4 0 Intelligent maintenance system Internet of Things Responsive computer aided design Signal flow graphReferences Edit US National Science Foundation Cyber Physical Systems CPS a b Hu J Lennox B Arvin F Robust formation control for networked robotic systems using Negative Imaginary dynamics Automatica 2022 a b Hu J Niu H Carrasco J Lennox B Arvin F Fault tolerant cooperative navigation of networked UAV swarms for forest fire monitoring Aerospace Science and Technology 2022 Hancu O Maties V Balan R Stan S 2007 Mechatronic approach for design and control of a hydraulic 3 dof parallel robot The 18th International DAAAM Symposium Intelligent Manufacturing amp Automation Focus on Creativity Responsibility and Ethics of Engineers Suh S C Carbone J N Eroglu A E Applied Cyber Physical Systems Springer 2014 Rad Ciprian Radu Hancu Olimpiu Takacs Ioana Alexandra Olteanu Gheorghe 2015 Smart Monitoring of Potato Crop A Cyber Physical System Architecture Model in the Field of Precision Agriculture Conference Agriculture for Life Life for Agriculture 6 73 79 a b Khaitan et al Design Techniques and Applications of Cyber Physical Systems A Survey IEEE Systems Journal 2014 C Alippi Intelligence for Embedded Systems Springer Verlag 2014 283pp ISBN 978 3 319 05278 6 Cyber physical systems Program Announcements amp Information The National Science Foundation 4201 Wilson Boulevard Arlington Virginia 22230 USA 2008 09 30 Retrieved 2009 07 21 Virtual Machine for running Java Applications on a CPS Retrieved 2012 04 12 White Jules Clarke S Dougherty B Thompson C Schmidt D R amp D Challenges and Solutions for Mobile Cyber Physical Applications and Supporting Internet Services PDF Springer Journal of Internet Services and Applications Archived from the original PDF on 2016 08 04 Retrieved 2011 02 21 J Froehlich T Dillahunt P Klasnja J Mankoff S Consolvo B Harrison and J Landay UbiGreen investigating a mobile tool for tracking and supporting green transportation habits in Proceedings of the 27th international conference on Human factors in computing systems ACM 2009 pp 1043 1052 P Handel I Skog J Wahlstrom F Bonawide R Welsh J Ohlsson and M Ohlsson Insurance telematics opportunities and challenges with the smartphone solution Intelligent Transportation Systems Magazine IEEE vol 6 no 4 pp 57 70 winter 2014 doi 10 1109 MITS 2014 2343262 Thompson C White J Dougherty B Schmidt D C 2009 Optimizing Mobile Application Performance with Model Driven Engineering PDF Software Technologies for Embedded and Ubiquitous Systems Lecture Notes in Computer Science Vol 5860 p 36 doi 10 1007 978 3 642 10265 3 4 ISBN 978 3 642 10264 6 Jones W D 2001 Forecasting traffic flow IEEE Spectrum 38 90 91 doi 10 1109 6 901153 Rose G 2006 Mobile Phones as Traffic Probes Practices Prospects and Issues Transport Reviews 26 3 275 291 doi 10 1080 01441640500361108 S2CID 109790299 Leijdekkers P 2006 Personal Heart Monitoring and Rehabilitation System using Smart Phones 2006 International Conference on Mobile Business p 29 doi 10 1109 ICMB 2006 39 hdl 10453 2740 ISBN 0 7695 2595 4 S2CID 14750674 S Karnouskos Cyber Physical Systems in the Smart Grid PDF 79 kB In Industrial Informatics INDIN 2011 9th IEEE International Conference on July 2011 Retrieved 20 Apr 2014 The Distributed Robotics Garden people csail mit edu 2011 Retrieved November 16 2011 Loukas George June 2015 Cyber Physical Attacks A growing invisible threat Oxford UK Butterworh Heinemann Elsevier p 65 ISBN 9780128012901 CarTel MIT Cartel cartel csail mit edu 2011 Archived from the original on August 11 2007 Retrieved November 16 2011 Liu R Srivastava A K Bakken D E Askerman A Panciatici P November December 2017 Decentralized State Estimation and Remedial Control Action for Minimum Wind Curtailment Using Distributed Computing Platform IEEE Transactions on Industry Applications 53 6 5915 doi 10 1109 TIA 2017 2740831 OSTI 1417238 A W Colombo T Bangemann S Karnouskos J Delsing P Stluka R Harrison F Jammes and J Lastra Industrial Cloud based Cyber Physical Systems The IMC AESOP Approach Springer Verlag 2014 ISBN 978 3 319 05623 4 Wu D Rosen D W Wang L Schaefer D 2014 Cloud Based Design and Manufacturing A New Paradigm in Digital Manufacturing and Design Innovation PDF Computer Aided Design 59 1 14 doi 10 1016 j cad 2014 07 006 S2CID 9315605 Wu D Rosen D W amp Schaefer D 2014 Cloud Based Design and Manufacturing Status and Promise In Schaefer D Ed Cloud Based Design and Manufacturing A Service Oriented Product Development Paradigm for the 21st Century Springer London UK pp 1 24 J Fitzgerald P G Larsen M Verhoef Eds Collaborative Design for Embedded Systems Co modelling and Co simulation Springer Verlag 2014 ISBN 978 3 642 54118 6 Wolf Wayne November 2007 The Good News and the Bad News Embedded Computing Column IEEE Computer 40 11 104 105 doi 10 1109 MC 2007 404 NSF Workshop On Cyber Physical Systems Archived from the original on 2008 05 17 Retrieved 2008 06 09 Beyond SCADA Networked Embedded Control for Cyber Physical Systems Archived from the original on January 17 2009 Retrieved 2008 06 09 NSF Cyber Physical Systems Summit Archived from the original on 2009 05 12 Retrieved 2008 08 01 National Workshop on High Confidence Automotive Cyber Physical Systems Archived from the original on 2008 08 27 Retrieved 2008 08 03 National Workshop on Composable and Systems Technologies for High Confidence Cyber Physical Systems Retrieved 2008 08 04 National Workshop on High Confidence Software Platforms for Cyber Physical Systems HCSP CPS Retrieved 2008 08 04 New Research Directions for Future Cyber Physical Energy Systems Retrieved 2009 06 05 Bridging the Cyber Physical and Social Worlds Archived from the original on 2012 07 16 Retrieved 2011 02 25 NIST Foundations for Innovation in Cyber Physical Systems Workshop Archived from the original on 2015 08 20 Retrieved 2012 02 08 Further reading EditEdward A Lee Cyber Physical Systems Are Computing Foundations Adequate Paulo Tabuada Cyber Physical Systems Position Paper Rajesh Gupta Programming Models and Methods for Spatio Temporal Actions and Reasoning in Cyber Physical Systems E A Lee and S A Seshia Introduction to Embedded Systems A Cyber Physical Systems Approach http LeeSeshia org 2011 Altawy R Youssef A Security Trade offs in Cyber Physical Systems A Case Study Survey on Implantable Medical Devices Ahmad I Security Aspects of Cyber Physical SystemsExternal links EditThe CPS Virtual Organization Cyber Physical Systems Week conference Illustrates current research in the area Transactions on Cyber Physical Systems ACM Journal in this area Retrieved from https en wikipedia org w index php title Cyber physical system amp oldid 1134138851, wikipedia, wiki, book, books, library,

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