Cyber-physical system

Cyber-physical system

A cyber-physical system (CPS) is a system featuring a tight combination of, and coordination between, the system’s computational and physical elements. Today, a pre-cursor generation 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. This generation 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.

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.[1] The notion is closely tied to concepts of robotics and sensor networks. Ongoing advances in science and engineering will improve the link between computational and physical elements, dramatically increasing the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems. This will broaden the potential of cyber-physical systems in several dimensions, 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., healthcare monitoring and delivery).[2]

The US National Science Foundation (NSF) has identified cyber-physical systems as a key area of research.[3] Starting in late 2006, the NSF and other United States federal agencies sponsored several workshops on cyber-physical systems.[4][5][6][7][8][9][10][11]

Contents

Mobile cyber-physical systems

Mobile cyber physical systems, in which the physical system in question 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, 3G, 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, Objective C, or C#
  • Readily-available application distribution mechanisms, such as the Android Market and Apple App Store
  • End-user maintenance and upkeep, including frequent re-charging of the battery

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.[12] Examples of mobile cyber-physical systems include applications to track and analyze CO2 emissions,[13] detect traffic accidents 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 systems and 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 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.[18]

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 designs, and considers the resilience aspects that are not well quantified, such as cyber security, human interaction and complex interdependencies.

Another example is MIT's ongoing CarTel project where a fleet of taxis 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.[19]

Cyber-physical society

The concept of a cyber-physical society[20][21][22] would encompass not only the cyber and physical spaces but also humans, knowledge, society and culture. The mental space, physiologial space and psychological space may be further considered in the cyber-physical-socio space to support cyber-physical socio intelligence.[23].

References

  1. ^ Lee, Edward (January 23, 2008). Cyber Physical Systems: Design Challenges. University of California, Berkeley Technical Report No. UCB/EECS-2008-8. http://www.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-8.html. Retrieved 2008-06-07. 
  2. ^ "Cyber-physical systems". Program Announcements & Information. The National Science Foundation, 4201 Wilson Boulevard, Arlington, Virginia 22230, USA. 2008-09-30. http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf08611. Retrieved 2009-07-21. 
  3. ^ Wolf, Wayne (November 2007). "The Good News and the Bad News (Embedded Computing Column". IEEE Computer 40 (11): 104. doi:10.1109/MC.2007.404. 
  4. ^ "NSF Workshop On Cyber-Physical Systems". http://varma.ece.cmu.edu/cps. Retrieved 2008-06-09. 
  5. ^ "Beyond SCADA: Networked Embedded Control for Cyber Physical Systems". http://www.truststc.org/scada/. Retrieved 2008-06-09. 
  6. ^ "NSF Cyber-Physical Systems Summit". http://varma.ece.cmu.edu/Summit. Retrieved 2008-08-01. 
  7. ^ "National Workshop on High-Confidence Automotive Cyber-Physical Systems". http://varma.ece.cmu.edu/Auto-CPS. Retrieved 2008-08-03. 
  8. ^ "National Workshop on Composable and Systems Technologies for High-Confidence Cyber-Physical Systems,". http://www.isis.vanderbilt.edu/CST-HCCPS/. Retrieved 2008-08-04. 
  9. ^ "National Workshop on High-Confidence Software Platforms for Cyber-Physical Systems (HCSP-CPS),". http://www.isis.vanderbilt.edu/HCSP-CPS/. Retrieved 2008-08-04. 
  10. ^ "New Research Directions for Future Cyber-Physical Energy Systems". http://www.ece.cmu.edu/~nsf-cps/. Retrieved 2009-06-05. 
  11. ^ "Bridging the Cyber, Physical, and Social Worlds". http://collaboration.greatplains.net/wiki/index.php/Workshop:_Bridging_the_Cyber,_Physical_and_Social_Worlds. Retrieved 2011-02-25. 
  12. ^ [|White, Jules]; Clarke, S., Dougherty, B., Thompson, C., and Schmidt, D.. "R&D Challenges and Solutions for Mobile Cyber-Physical Applications and Supporting Internet Services". Springer Journal of Internet Services and Applications. http://www.cs.wustl.edu/~schmidt/PDF/jisa-2010-paper.pdf. Retrieved 2011-02-21. 
  13. ^ 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.
  14. ^ C. Thompson, J. White, B. Dougherty, and D. Schmidt, “Optimizing Mobile Ap- plication Performance with Model-Driven Engineering,” in Proceedings of the 7th IFIP Workshop on Software Technologies for Future Embedded and Ubiquitous Sys- tems, 2009
  15. ^ W. Jones, “Forecasting traffic flow,” IEEE Spectrum, vol. 38, no. 1, pp. 90–91, 2001.
  16. ^ G. Rose, “Mobile phones as traffic probes: practices, prospects and issues,” Trans- port Reviews, vol. 26, no. 3, pp. 275–291, 2006
  17. ^ P. Leijdekkers and V. Gay, “Personal heart monitoring and rehabilitation system using smart phones,” in Proceedings of the International Conference on Mobile Business. Citeseer, 2006, p. 29
  18. ^ "The Distributed Robotics Garden". people.csail.mit.edu. 2011 [last update]. http://people.csail.mit.edu/nikolaus/drg/. Retrieved November 16, 2011. 
  19. ^ {{cite web |url= http://cartel.csail.mit.edu/doku.php |title=CarTel [MIT Cartel] |first= |last=
  20. ^ Zhuge, H. (2010). "Interactive Semantics". Artificial Intelligence 174 (2): 190–204. doi:10.1016/j.artint.2009.11.014. 
  21. ^ H.Zhuge and Y.Xing, "Probabilistic Resource Space Model for Managing Resources in Cyber-Physical Society," IEEE Transactions on Service Computing, http://doi.ieeecomputersociety.org/10.1109/TSC.2011.12.
  22. ^ H.Zhuge, "Cyber Physical Society," the 1st Workshop on Cyber Physical Society, in conjunction with the 6th International Conference on Semantics, Knowledge and Grids, Ningbo, China, 2010.
  23. ^ Zhuge, H. (2011). "Semantic linking through spaces for cyber-physical-socio intelligence: A methodology". Artificial Intelligence 175 (5–6): 988–1019. doi:10.1016/j.artint.2010.09.009. 

Further reading

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