Advertisement

Cognitive Technologies in Monitoring Management

  • A. I. VodyahoEmail author
  • V. Yu. OsipovEmail author
  • N. A. ZhukovaEmail author
  • M. A. ChervontsevEmail author
Information Systems
  • 3 Downloads

Abstract

The concept of cognitive monitoring is defined. Some possible approaches to the construction of cognitive monitoring systems are considered and their generalized structure is described. The concept of a cognitive monitoring machine is introduced. A cognitive architecture approach to design monitoring systems that features the generation of on-demand architectures is proposed. The structure of a platform oriented to the use of this approach is described. An example of creating a cognitive monitoring system is considered.

Keywords

cognitive systems monitoring systems and cognitive architecture approach to monitoring system design 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
  2. 2.
    Kelly, J.E., Smart machines: IBM’s Watson and the Era of Cognitive Computing, Columbia Business School Publishing. https://doi.org/www.delaat.net/smartnetworks/files/watson%20papers/l46316241-Smart-Machines-IBM%E2%80%99s-Watson-and-the-Era-of-Cognitive-Computing.pdf.
  3. 3.
    Balani, N., Cognitive IoT, 2015. https://doi.org/navveenbalani.com/.
  4. 4.
    Schatsky, D., Muraskin, C., and Gurumurthy, R., Cognitive technologies: The real opportunities for business, Deloitte Rev., 2015, no. 16, pp. 115–129.Google Scholar
  5. 5.
    International Standard ISO/IEC/IEEE 42010 Systems and Software Engineering: Architecture Description. https://doi.org/www.iso.org/standard/50508.html.
  6. 6.
    How is cognitive computing different from big data and NLP? https://doi.org/coseer.com/blog/how-is-cognitive-computing-different-from-big-data-and-nlp/.
  7. 7.
    Russell, S. and Norvig, P., Artificial Intelligence: A Modern Approach, Upper Saddle River, NJ, 2010, 3rd ed.Google Scholar
  8. 8.
    Sangaiah, A.K., Thangavelu, A., and Sundaram, V.M.S., Cognitive Computing for Big Data Systems over IoT. Frameworks, Tools and Applications, Cham (Switzerland): Springer, 2018.CrossRefGoogle Scholar
  9. 9.
    Bass, L., Clements, P., and Kazman, R., Software Architecture in Practice, Upper Saddle River, NJ: Addison-Wesley, 2013, 3rd ed.Google Scholar
  10. 10.
    Okhtilev, M.Yu., Sokolov, B.V., and Yusupov, R.M., Intellektual’nye tekhnologii monitoringa sostoyaniya i upravleniya strukturnoi dinamikoi slozhnykh tekhnicheskikh ob”ektov (Intelligent Technologies for Monitoring the State and Control of the Structural Dynamics of Complex Technical Objects), Moscow: Nauka, 2005.Google Scholar
  11. 11.
    Blasch, E., Bosse, E., and Lambert, D., High-Level Information Fusion Management and System Design, Norwood, MA: Artech House Publishers, 2012.Google Scholar
  12. 12.
    Gasevic, D., Djuric, D., Devedzic, V., Model Driven Architecture and Ontology Development, Berlin-Heidelberg: Springer-Verlag, 2006.Google Scholar
  13. 13.
    Sommerville, I., Software Engineering, Boston, MA: Addison-Wesley, 2011.zbMATHGoogle Scholar
  14. 14.
    Zaki, M. and Meira, W., Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge: Cambridge Univ. Press, 2014.CrossRefzbMATHGoogle Scholar
  15. 15.
    van der Aalst, W., Process Mining. Data Science in Action, Berlin-Heidelberg: Springer-Verlag, 2016, 2nd ed.CrossRefGoogle Scholar
  16. 16.
    Osipov, V.Yu., Automatic synthesis of action programs for intelligent robots, Program. Comput. Software, 2017, vol. 2016, no. 42, pp. 3–155.MathSciNetGoogle Scholar
  17. 17.
    Zivin, B.E., Jouault, J., and Valduriez, P., On the need for megamodels. https://doi.org/scinapse.io/papers/195085068.
  18. 18.
    Babar, M.A., Brown, A.W., and Mistrik, I., Agile Software Architecture, Waltham, MA: Elsevier, 2014.Google Scholar
  19. 19.
    Kelly, S. and Tolvanen, J., Domain-Specific Modeling: Enabling Full Code Generation, London: John Wiley & Sons, 2008.CrossRefGoogle Scholar
  20. 20.
    Vodyaho, A.I., Mustafin, N.G., and Zhukova, N.A., The ontological approach to building systems for resources monitoring in cable television networks, Izv. S.-Peterb. Gos. Elektrotekh. Univ., 2017, no. 2, pp. 29–38.Google Scholar

Copyright information

© Allerton Press, Inc. 2019

Authors and Affiliations

  1. 1.St. Petersburg Electrotechnical UniversitySt. PetersburgRussia
  2. 2.St. Petersburg Institute for Informatics and AutomationRussian Academy of SciencesSt. PetersburgRussia

Personalised recommendations