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Infrastructure and Complex Systems Automation

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Abstract

The set of traditional characteristic features of large-scale complex systems (LSS) included the large number of variables, structure of interconnected subsystems, and other features that complicate the control models, such as nonlinearities, time delays, and uncertainties. The advances in information and communication technologies (ICT) and the modern business models have led to important evolution in the concepts and the corresponding management and control infrastructures of large-scale complex systems. The last three decades have highlighted several new characteristic features, such as networked structure, enhanced geographical distribution associated with the increased cooperation of subsystems, evolutionary development, higher risk sensitivity, presence of more, possibly conflicting, objectives, and security and environment concerns. This chapter aims to present a balanced review of several traditional well-established methods (such as multilevel and decentralized control) and modern control solutions (such as cooperative and networked control) for LSS together with the technology development and new application domains, such as smart city with heating and water distribution systems, and environmental monitoring and protection. A particular attention is paid to automation infrastructures and associated enabling technologies together with security aspects.

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References

  1. Tomovic, R.: Control of large systems. In: Troch, I. (ed.) Simulation of Control Systems, pp. 3–6. North Holland, Amsterdam (1972)

    Google Scholar 

  2. Mahmoud, M.S.: Multilevel systems control and applications. IEEE Trans. Syst. Man Cybern. SMC–7, 125–143 (1977)

    MathSciNet  MATH  Google Scholar 

  3. Šiljak, D.D.: Large Scale Dynamical Systems: Stability and Structure. North Holland, Amsterdam (1978)

    MATH  Google Scholar 

  4. Athans, M.: Advances and open problems on the control of large-scale systems, Plenary paper. In: Proc. 7th IFAC Congress, pp. 2371–2382. Pergamon Press, Oxford (1978)

    Google Scholar 

  5. Jamshidi, M.: Large Scale Systems: Modeling and Control. North Holland, New York (1983); 2nd edn. Prentice Hall, Upper Saddle River (1997)

    Google Scholar 

  6. Mesarovic, M.D., Macko, D., Takahara, Y.: Theory of Hierarchical Multilevel Systems. Academic, New York (1970)

    MATH  Google Scholar 

  7. Filip, F.G., Dumitrache, I., Iliescu, S.S.: Foreword. In: Proceedings of the 9th IFAC Symposium on Large Scale Systems: Theory and Applications 2001, Bucharest, Romania, 18–20 July 2001, pp. V-VII. IFAC Proceedings Volumes 3 (8) (2001). https://www.sciencedirect.com/journal/ifac-proceedings-volumes/vol/34/issue/8. Accessed 10 Aug 2020

  8. Findeisen, W.: Decentralized and hierarchical control under consistence or disagreements of interests. Automatica. 18(6), 647–664 (1982)

    MathSciNet  MATH  Google Scholar 

  9. Takatsu, S.: Coordination principles for two-level satisfactory decision-making systems. Syst. Sci. 7(3/4), 266–284 (1982)

    MathSciNet  Google Scholar 

  10. Filip, F.G., Donciulescu, D.A.: On an online dynamic coordination method in process industry. IFAC J. Automat. 19(3), 317–320 (1983)

    Google Scholar 

  11. Mårtenson, L.: Are operators in control of complex systems? In: Proc. 13th IFAC World Congress, vol. B, pp. 259–270. Pergamon, Oxford (1990)

    Google Scholar 

  12. Nof, S.Y., Morel, G., Monostori, L., Molina, A., Filip, F.G.: From plant and logistics control to multi-enterprise collaboration. Milestones report of the manufacturing & logistic systems coordinating committee. Annu. Rev. Control. 30(1), 55–68 (2006)

    Google Scholar 

  13. Stahel, W.R.: The circular economy. Nature. 531, 435–438 (2016). https://doi.org/10.1038/531435a

    Article  Google Scholar 

  14. Ilgin, M.A., Gupta, S.M.: Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art. J. Environ. Manag. 91, 563–559 (2010)

    Google Scholar 

  15. Duta, L., Filip, F.G.: Control and decision-making process in disassembling used electronic products. Stud. Inform. Control. 17(1), 17–26 (2008)

    Google Scholar 

  16. Gupta, S.M., Ilgin, A.M.: Multiple Criteria Decision-Making Applications in Environmentally Conscious Manufacturing and Product Recovery. CRC Press, Boca Raton (2018)

    Google Scholar 

  17. Sage, A.P., Cuppan, C.D.: On the system engineering of systems of systems and federations of systems. Inf. Knowl. Syst. Manage. 2(4), 325–349 (2001)

    Google Scholar 

  18. Gheorghe, A.V., Vamanu, D.V., Katina, P.F., Pulfer, R.: Critical infrastructures, key resources, and key assets. In: Critical Infrastructures, Key Resources, Key Assets. Topics in Safety, Risk, Reliability and Quality, vol. 34. Springer, Cham (2018)

    Google Scholar 

  19. Donciulescu, D.A., Filip, F.G.: DISPECER-H – a decision supporting system in water resources dispatching. Annu. Rev. Autom. Program. 12(2), 263–266 (1985)

    Google Scholar 

  20. Lee, E.A.: Cyber physical systems: design challenges. In: 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC), Orlando, pp. 363–369 (2008)

    Google Scholar 

  21. Yilma, B., Panetto, H., Naudet, Y.: A meta-model of cyber-physical-social system: the CPSS paradigm to support human-machine collaboration in Industry 4.0. Collab. Netw. Digital Transform. 568, 11–20 (2019)

    Google Scholar 

  22. Nof, S.Y., Morel, G., Monostori, L., Molina, A., Filip, F.: From plant and logistic control to multienterprise. milestones report of the manufacturing & logistic systems coordinating committee. Annu. Rev. Control. 30(1), 55–68 (2006)

    Google Scholar 

  23. Nof, S.Y., Ceroni, J., Jeong, W., Moghaddam, M.: Revolutionizing Collaboration through e-Work, e-Business, and e-Service. Springer, Berlin/Heidelberg (2015)

    Google Scholar 

  24. Zhong, H., Nof, S.Y.: Collaborative e-work and collaborative control theory for disruption handling and control. In: Dynamic Lines of Collaboration. Automation, Collaboration, & E-Services, vol. 6, pp. 23–31. Springer, Cham (2020)

    Google Scholar 

  25. Romero, D., Bernus, P., Noran, O., Stahre, J., Fast-Berglund, Å.: The Operator 4.0: human cyber-physical systems & adaptive automation towards human-automation symbiosis. In: Nääs, I., et al. (eds.) Advances in Production Management Systems. Initiatives for a Sustainable World. APMS 2016. IFIP AICT, vol. 488. Springer (2016)

    Google Scholar 

  26. Vernadat, F.B., Chen, F.T.S., Molina, A., Nof, S.Y., Panetto, H.: Information systems and knowledge management in industrial engineering: recent advances and new perspectives. Int. J. Prod. Res. 56(8), 2707–2713 (2018)

    Google Scholar 

  27. Borangiu, T., Morariu, O., Raileanu, S., Trentesaux, D., Leitão, P., Barata, J.: Digital transformation manufacturing. Industry of the future with cyber-physical production systems. ROMJIST. 23(1), 3–37 (2020)

    Google Scholar 

  28. Camarinha-Matos, L.M., Fornasiero, R., Ramezani, J., Ferrada, F.: Collaborative networks: a pillar of digital transformation. Appl. Sci. 9, 5431 (2019)

    Google Scholar 

  29. Ledet, W.P., Himmelblau, D.M.: Decomposition procedures for the solving of large scale systems. Adv. Chem. Eng. 8, 185–254 (1970)

    Google Scholar 

  30. Šiljak, D.D.: Decentralized Control of Complex Systems. Academic, New York (1991)

    MATH  Google Scholar 

  31. Obinata, G., Anderson, B.D.O.: Model reduction for control system design. In: Series Communications and Control Engineering. Springer, London (2001)

    Google Scholar 

  32. Kokotović, P.V.: Applications of singular perturbation techniques to control problems. SIAM Rev. 26(4), 501–555 (1984)

    MathSciNet  MATH  Google Scholar 

  33. Antsaklis, P.J., Passino, K.M. (eds.): An Introduction to Intelligent and Autonomous Control. Kluwer Academic (1993)

    MATH  Google Scholar 

  34. Precup, R.E., Hellendoorn, H.: A survey on industrial applications of fuzzy control. Comput. Ind. 62(3), 213–226 (2011)

    Google Scholar 

  35. Binder, Z.: Sur l’organisation et la conduite des systèmes complexes. Thèse de Docteur. LAG, Grenoble (1977)

    Google Scholar 

  36. Lupu, C., Borne, P., Popescu, D.: Multi-model adaptive control systems. CEAI. 10(1), 49–56 (2008)

    Google Scholar 

  37. Liu, Y.-Y., Barabási, A.-L.: Control principles of complex systems. Rev. Mod. Phys. 88, 035006 (2016)

    Google Scholar 

  38. Hespanha, J.P., Naghshtabriz, P., Xu, Y.G.: A survey of recent results in networked control systems. Proc. IEEE. 95(1), 138–162 (2007)

    Google Scholar 

  39. Mahmoud, M.S., Hamdan, M.M.: Fundamental issues in networked control systems. IEEE/CAA J. Automat. Sin. 5(5), 902–922 (2018)

    MathSciNet  Google Scholar 

  40. Ho, Y.C., Mitter, S.K.: Directions in Large-Scale Systems. Plenum, New York (1976)

    Google Scholar 

  41. Sage, A.P.: Methodology for Large Scale Systems. McGraw Hill, New York (1977)

    MATH  Google Scholar 

  42. Singh, M.D., Titli, A.: Systems: Decomposition, Optimisation, and Control. Pergamon, Oxford (1978)

    MATH  Google Scholar 

  43. Findeisen, W., Brdys, M., Malinowski, K., Tatjewski, P., Wozniak, A.: Control and Coordination in Hierarchical Systems. Wiley, Chichester (1980)

    MATH  Google Scholar 

  44. Brdys, M., Tatjewski, P.: Iterative Algorithms for Multilayer Optimizing Control. Imperial College, London (2001)

    MATH  Google Scholar 

  45. Steward, D.: Systems Analysis and Management: Structure, Strategy and Design. Petrocelli Books, New York (1981)

    Google Scholar 

  46. Schoeffler, J.: Online multilevel systems. In: Wismer, D. (ed.) Optimization Methods for Large Scale Systems, pp. 291–330. McGraw Hill, New York (1971)

    Google Scholar 

  47. Nam, T., Pardo, T.A.: Conceptualizing smart city with dimensions of technology, people, and institutions. In: dg.o ‘11, Proc. 12th Annu. Intern. Digital Gov. Res. Conf: Digital Government Innovation in Challenging Times, June 2011, pp. 282–291 (2011)

    Google Scholar 

  48. Eckman, P., Lefkowitz, I.: Principles of model technique in optimizing control. In: Proc. 1st IFAC World Congr., Moscow 1960, pp. 970–974 (1960)

    Google Scholar 

  49. Lefkowitz, I.: Multilevel approach to control system design. In: Proc. JACC, pp. 100–109 (1965)

    Google Scholar 

  50. Grassi, A., Guizzi, G., Santillo, L.C., Vespoli, S.: A semi-heterarchical production control architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 24, 43–46 (2020)

    Google Scholar 

  51. Kim, D.-S., Tran-Dang, H.: Industrial sensors and controls in communication networks. Comput. Commun. Netw. (2019). https://doi.org/10.1007/978-3-030-04927-0_1

  52. Brosilow, C.B., Ladson, L.S., Pearson, J.D.: Feasible optimization methods for interconnected systems. In: Proc. Joint Autom. Control Conf. – JACC, pp. 79–84. Rensselaer Polytechnic Institute, Troy/New York (1965)

    Google Scholar 

  53. Williams, T.J.: Analysis and Design of Hierarchical Control Systems with Special Reference to Steel Plant Operations. Elsevier, Amsterdam (1985)

    Google Scholar 

  54. Hatvany, J.: Intelligence and cooperation in heterarchic manufacturing systems. Robot. Comput. Integr. Manuf. 2(2), 101–104 (1985)

    Google Scholar 

  55. Rey, G.Z., Pach, C., Aissani, N., Berger, T., Trentesaux, D.: The control of myopic behavior in semi-heterarchical production systems: a holonic framework. Eng. Appl. Artif. Intell. 26(2), 800–817 (2013)

    Google Scholar 

  56. Koestler, A.: The Ghost in the Machine. Hutchinson, London (1967)

    Google Scholar 

  57. Hopf, M., Schoeffer, C.F.: Holonic manufacturing systems. In: Goossenaerts, J., et al. (eds.) Information Infrastructure Systems for Manufacturing, pp. 431–438. Springer Science+Business Media, Dordrecht (1997)

    Google Scholar 

  58. Filip, F.G., Leiviskä, K.: Large-scale complex systems. In: Nof, S.Y. (ed.) Springer Handbook of Automation, pp. 619–638. Springer, Berlin/Heidelberg (2009)

    Google Scholar 

  59. Valckenaers, P., Van Brussel, H., Hadeli, K., Bochmann, O., Germain, B.S., Zamfirescu, C.: On the design of emergent systems an investigation of integration and interoperability issues. Eng. Appl. Artif. Intell. 16, 377–393 (2003)

    Google Scholar 

  60. Parunak, H.V.D.: Practical and Industrial Applications of Agent-Based Systems. Industrial Technology Institute, Ann Arbor (1998)

    Google Scholar 

  61. Tecuci, G., Dybala, T.: Building Intelligent Agents: An Apprenticeship Multistrategy Learning Theory, Methodology, Tool and Case Studies. Academic, New York (1998)

    Google Scholar 

  62. Nof, S.Y.: Collaborative control theory for e-work, e-production and e-service. Annu. Rev. Control. 31(2), 281–292 (2007)

    Google Scholar 

  63. Monostori, L., Valkenaerts, P., Dolgui, A., Panetto, H., Brdys, M., Csáji, B.C.: Cooperative control in production and logistics. Annu. Rev. Control. 39, 12–29 (2015)

    Google Scholar 

  64. Siljak, D.: Decentralized Control of Complex Systems. Dover Publications, Mineola (2012) Original Academic Press (1991)

    Google Scholar 

  65. Davison, E.J., Aghdam, A.G., Miller, D.: Decentralized Control of Large-Scale Systems. Springer, New York (2020)

    MATH  Google Scholar 

  66. Wang, S.-H., Davison, E.J.: On the stabilization of decentralized control system. IEEE Trans. Autom. Control. 18(5) (1973)

    Google Scholar 

  67. Bakule, L.: Decentralized control: an overview. Annu. Rev. Control. 32, 87–98 (2008)

    Google Scholar 

  68. Inagaki, T.: Adaptive automation: sharing and trading of control. In: Hollnagel, E. (ed.) Handbook of Cognitive Task Design, pp. 147–169. LEA (2003)

    Google Scholar 

  69. Fitts, P.M.: Human Engineering for an Effective Air Navigation and Traffic Control System. Nat. Res. Council, Washington, DC (1951)

    Google Scholar 

  70. Flemisch, F., Heesen, M., Hesse, T., Kelsch, J., Schieben, A., Beller, J.: Towards a dynamic balance between humans and automation: authority, ability, responsibility, and control in shared and cooperative control situations. Cogn. Tech. Work. 14(1), 3–8 (2012)

    Google Scholar 

  71. Bibby, K.S., Margulies, F., Rijnsdorp, J.E., Whithers, R.M.: Man’s role in control systems. In: Proceedings, IFAC 6th Triennial World Congress, Boston, Cambridge, MA, pp. 24–30 (1975)

    Google Scholar 

  72. Bainbridge, L.: Ironies of automation. IFAC J. Automatica. 19(6), 775–779 (1983)

    Google Scholar 

  73. Martin, T., Kivinen, J., Rijnsdorp, J.E., Rodd, M.G., Rouse, W.B.: Appropriate automation – integrating human, organizational, economic, and cultural factors. In: Proc. IFAC 11th World Congress, vol. 23, issue 8, Part 1, pp. 1–19 (1990)

    Google Scholar 

  74. Schneiderman, B.: Human-centered artificial intelligence: reliable, safe & trustworthy. Int. J. Human–Comput. Interact. 36(6), 495–504 (2020)

    Google Scholar 

  75. Power, D.J., Heavin, C., Keenan, P.: Decision systems redux. J. Decis. Syst. 28(1), 1–18 (2019)

    Google Scholar 

  76. Filip, F.G., Suduc, A.M., Bizoi, M.: DSS in numbers. Technol. Econ. Dev. Econ. 20(1), 154–164 (2014)

    Google Scholar 

  77. Filip, F.G.: Decision support and control for large-scale complex systems. Annu. Rev. Control. 32(1), 62–70 (2008)

    Google Scholar 

  78. Filip, F.G.: DSS – a class of evolving information systems. In: Dzemyda, G., Bernatavičienė, J., Kacprzyk, J. (eds.) Data Science: New Issues, Challenges and Applications. Studies in Computational Intelligence, vol. 869, pp. 253–277. Springer, Cham (2020)

    Google Scholar 

  79. Nof, S.Y.: Theory and practice in decision support for manufacturing control. In: Holsapple, C.W., Whinston, A.B. (eds.) Data Base Management, pp. 325–348. Reidel, Dordrecht (1981)

    Google Scholar 

  80. Filip, F.G., Neagu, G., Donciulescu, D.A.: Jobshop scheduling optimization in real-time production control. Comput. Ind. 4(3), 395–403 (1983)

    Google Scholar 

  81. Cioca, M., Cioca, L.-I.: Decision support systems used in disaster management. In: Jao, C.S. (ed.) Decision Support Systems, pp. 371–390. INTECH (2010). https://doi.org/10.5772/39452

    Chapter  Google Scholar 

  82. Charturverdi, A.R., Hutchinson, G.K., Nazareth, D.J.: Supporting real-time decision-making through machine learning. Decis. Support. Syst. 10, 213–233 (1997)

    Google Scholar 

  83. Simon, H.: Rational choice and the structure of environment. Psychol. Rev. 63(2), 129–138 (1956)

    Google Scholar 

  84. Van de Walle, B., Turoff, M.: Decision support for emergency situations. Inf. Syst. E-Bus. Manage. 6, 295–316 (2008)

    Google Scholar 

  85. Filip, F.G., Zamfirescu, C.B., Ciurea, C.: Computer-Supported Collaborative Decision-Making. Springer, Cham (2017)

    Google Scholar 

  86. Candea, C., Filip, F.G.: Towards intelligent collaborative decision support platforms. Stud. Inform. Control. 25(2), 143–152 (2016)

    Google Scholar 

  87. Nof, S.Y.: Collaborative control theory and decision support systems. Comput. Sci. J. Moldova. 25(2), 15–144 (2017)

    Google Scholar 

  88. Ding, R.X., Palomares, I., Wang, X., Yang, G.-R., Liu, B., Dong, Y., Herrera-Viedma, E., Herrera, F.: Large-scale decision-making: characterization, taxonomy, challenges and future directions from an artificial intelligence and applications perspective. Inform. Fusion. 59, 84–102 (2020)

    Google Scholar 

  89. Bonczek, R.H., Holsapple, C.W., Whinston, A.B.: Foundations of Decision Support Systems. Academic, New York (1981)

    MATH  Google Scholar 

  90. Holsapple, C.W., Whinston, A.B.: Decision Support System: A Knowledge-Based Approach. West Publishing, Minneapolis (1996)

    Google Scholar 

  91. Simon, H.: Two heads are better than one: the collaboration between AI and OR. Interfaces. 17(4), 8–15 (1987)

    Google Scholar 

  92. Kusiak, A., Chen, M.: Expert systems for planning and scheduling manufacturing systems. Eur. J. Oper. Res. 34(2), 113–130 (1988)

    MathSciNet  Google Scholar 

  93. Filip, F.G.: System analysis and expert systems techniques for operative decision making. J. Syst. Anal. Model. Simul. 8(2), 296–404 (1990)

    Google Scholar 

  94. Kaklauskas, A.: Biometric and Intelligent Decision-Making Support. Springer International Publishing, Cham (2015)

    Google Scholar 

  95. Zaraté, P., Liu, S.: A new trend for knowledge-based decision support systems design. Int. J. Inform. Decis. Sci. 8(3), 305–324 (2016)

    Google Scholar 

  96. Dutta, A.: Integrated AI and optimization for decision support: a survey. Decis. Support. Syst. 18, 213–226 (1996)

    Google Scholar 

  97. Engelbart, D.C.: Augmenting Human Intellect: a Conceptual Framework. SRI Project 3578 (1962). https://apps.dtic.mil/dtic/tr/fulltext/u2/289565.pdf. Accessed 10 Aug 2020

  98. Hollnagel, E., Woods, D.D.: Cognitive systems engineering: new wine in new bottles. Int. J. Man-Mach. Stud. 18(6), 583–600 (reprinted in Intern J Human-Comp Stud 51:339–356) (1983/1999)

    Google Scholar 

  99. Kelly III, J.E.: Computing, Cognition and the Future of Knowing. How Humans and Machines are Forging a New Age of Understanding. IBM Global Service (2015)

    Google Scholar 

  100. Siddike, M.A.K., Spohrer, J., Demirka, H., Kohda, J.: People’s interactions with cognitive assistants for enhanced performances. In: Proc. 51st International Conference on System Sciences, pp. 1640–1648 (2018)

    Google Scholar 

  101. Rouse, W.B., Spohrer, J.C.: Automating versus augmenting intelligence. J. Enterprise Transform. (2018). https://doi.org/10.1080/19488289.2018.1424059

  102. AIHLEG: Ethics Guidelines for Trustworthy AI. European Commission (2019). https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines#Top. Accessed 10 Aug 2020

  103. Rouse, M.: Definition: Internet of Things (IoT). IoT Agenda (2020). https://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT. Accessed 30 June 2020

  104. Jeschke, S., Brecher, C., Meisen, D., Özdemir, D., Eschert T.: Industrial Internet of Things and Cyber Manufacturing Systems. Springer Series in Wireless Technology (2017)

    Google Scholar 

  105. Boyes, H., Hallaq, B., Cunningham, J., Watson, T.: The industrial internet of things (IIoT): an analysis framework. Comput. Ind. 101, 1–12 (2018)

    Google Scholar 

  106. Erboz, G.: How to define Industry4.0: the main pillars of industry 4.0. In: Conference Managerial Trends in the Development of Enterprises in Globalization Era, at Slovak University of Agriculture in Nitra, Slovakia, pp. 761–767 (2017)

    Google Scholar 

  107. Mell, P., Grance, T.: The NIST definition of cloud computing. Special publication 800-15. (2011). http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf. Accessed 30 June 2020

  108. Hamilton, E.: What Is Edge Computing: The Network Edge Explained. (2018). https://www.cloudwards.net/what-is-edge-computing. Accessed 30 June 2020

  109. ISO/IEC 18384:2016. 2016. Information Technology - Reference Architecture for Service Oriented Architecture (SOA RA). Geneva: International Organization for Standardization

    Google Scholar 

  110. Moghaddam, M., and Nof, S.Y. Collaborative service-component integration in cloud manufacturing, Int. J. of Prod. Res., 56(1-2), 677–691 (2018)

    Google Scholar 

  111. Shi, W., Cao, J., Zhang, Q., Li, T., Xu, L.: Edge computing: vision and challenges. IEEE Internet Things J. 3(5) (2016)

    Google Scholar 

  112. Dinh, H.T., Lee, C., Niyato, D., Wang, P.: A survey of mobile cloud computing: architecture, applications, and approaches. Wirel. Commun. Mob. Comput. 13, 1587–1611 (2013)

    Google Scholar 

  113. Mao, Y., You, C., Zhang, J., Huang, K., Letaief, K.B.: Mobile edge computing: survey and research outlook. Research Gate. (2017). https://www.researchgate.net/publication/312061424_Mobile_Edge_Computing_Survey_and_Research_Outlook Accessed 4 July 2020

  114. Gangula, A., Ansari, S., Gondhalekar, M.: Survey on mobile computing security. In: 2013 European Modelling Symposium, Manchester, pp. 536–542 (2013)

    Google Scholar 

  115. Baheti, R., Gill H.: Cyber-physical systems. (2011). http://ieeecss.org/sites/ieeecss/files/2019-07/IoCT-Part3-02CyberphysicalSystems.pdf. Accessed 10 July 2020

  116. Lee, J., Bagheri, B., Kao, H.-A.: A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18–23 (2015)

    Google Scholar 

  117. Khaitan, S., McCalley, J.D.: Design techniques and applications of cyberphysical systems: a survey. IEEE Syst. J. 9(2), 350–365 (2015)

    Google Scholar 

  118. Tao, F., Qi, Q., Wang, L., Nee, A.Y.C.: Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: correlation and comparison. Engineering. 5, 653–661 (2019)

    Google Scholar 

  119. Grimes, S.: Big Data: avoid ‘Wanna V’ confusion. Information Week (2013)

    Google Scholar 

  120. Alexandru, A., Alexandru, C.A., Coardos, D., Tudora, E.: Big Data: concepts, technologies and applications in the public sector. Int. J. Comput. Inf. Eng. 10(10), 1670–1676 (2016)

    Google Scholar 

  121. IBM: What is Big Data? https://www.ibm.com/analytics/hadoop/big-data-analytics. Accessed 16 July (2020)

  122. Reis, M.S., Gins, G.: Industrial process monitoring in the Big Data/Industry 4.0 era: from detection, to diagnosis, to prognosis. PRO. 5(35) (2017)

    Google Scholar 

  123. Li, A., Liu, Y.-Y.: Controlling network dynamics. Adv. Complex Syst. 22(07n08), 1950021 (2019)

    MathSciNet  Google Scholar 

  124. Antsaklis, P., Baillieul, J.: Special issue on technology of networked control systems. Proc. IEEE. 95(1), 5–8 (2007)

    Google Scholar 

  125. Murray, R.M., Åström, K.J., Boyd, S.P., Brockett, R.W., Stein, G.: Future directions in control in an information-rich world. IEEE Control. Syst. Mag. 20–33 (2003)

    Google Scholar 

  126. Sandberg, H., Amin, S., Johansson, K.H.: Cyberphysical security in networked control systems: an introduction to the issue. IEEE Control. Syst. Mag. 35(1), 20–23 (2015)

    MathSciNet  MATH  Google Scholar 

  127. Zhang, X.-M., Han, Q.-L., Ge, X., Ding, D., Ding, L., Yue, D., Peng, C.: Networked control systems: a survey of trends and techniques. IEEE/CAA J Automat. Sin. 7(1), 1–17 (2020)

    MathSciNet  Google Scholar 

  128. Zhan, Y., Xia, Y., Vasilakos, A.V.: Future directions of networked control systems: a combination of cloud control and fog control approach. Comput. Netw. 161(9), 235–248 (2019)

    Google Scholar 

  129. Xia, Y.: Cloud control systems. IEEE/CAA J. Automat. Sin. 2(2), 134–142 (2015)

    MathSciNet  Google Scholar 

  130. Kunal, S., Saha, A., Amin, R.: An overview of cloud-fog computing: architectures, applications with security challenges. Secur. Privacy 2(4), 14 p. (2019)

    Google Scholar 

  131. Open Fog: OpenFog Reference Architecture for Fog Computing (2017). https://www.iiconsortium.org/pdf/OpenFog_Reference_Architecture_2_09_17.pdf Accessed 10 Aug 2020

  132. Atlam, H.F., Walters, R.J., Wills, G.B.: Fog computing and the internet of things: a review. Big Data Cogn. Comput. 2(10) (2018)

    Google Scholar 

  133. Rad, B.B., Shareef, A.A.: Fog computing: a short review of concept and applications. IJCSNS Int. J. Comput. Sci. Netw. Secur. 17(11), 68–74 (2017)

    Google Scholar 

  134. Satyanarayanan, M.: The emergence of edge computing. Computer. 50(1), 30–39 (2017). https://doi.org/10.1109/MC.2017.9

    Article  Google Scholar 

  135. Basir, R., Qaisar, S., Ali, M., Aldwairi, M., Ashraf, M.I., Mahmood, A., Gidlund, M.: Fog computing enabling industrial internet of things: State-of-the-art and research challenges. Big Data Cogn. Comput. 2(10) (2018). https://doi.org/10.3390/bdcc2020010

  136. Louis, J.-N., Caló, A., Leiviskä, K., Pongrácz, E.: Modelling home electricity management for sustainability: the impact of response levels, technological deployment & occupancy. Energ. Buildings. 119, 218–232 (2016)

    Google Scholar 

  137. Hietaharju, P., Ruusunen, M., Leiviskä, K., Paavola, M.: Predictive optimization of the heat demand in buildings at the city level. Appl. Sci. 9, 16 p. (2019)

    Google Scholar 

  138. Louis, J.-N., Caló, A., Leiviskä, K., Pongrácz, E.: Environmental impacts and benefits of smart home automation: life cycle assessment of home energy management system. In: Breitenecker, F., Kugi, A., Troch, I. (eds.) 8th Vienna International Conference on Mathematical Modelling – MATHMOD 2015, pp. 880–885. IFAC-PapersOnLine, Vienna (2015)

    Google Scholar 

  139. Louis, J.-N., Caló, A., Leiviskä, K., Pongrácz, E.: A methodology for accounting the co2 emissions of electricity generation in Finland – the contribution of home automation to decarbonisation in the residential sector. Int. J. Adv. Intell. Syst. 8(3&4), 560–571 (2014)

    Google Scholar 

  140. Hietaharju, P., Ruusunen, M., Leiviskä, K.: A dynamic model for indoor temperature prediction in buildings. Energies. 11, 1477 (2018)

    Google Scholar 

  141. Hietaharju, P., Ruusunen, M.: Peak load cutting in district heating network. In: Proceedings of the 9th EUROSIM Congress on Modelling and Simulation, Oulu, Finland, 12–16 September (2016)

    Google Scholar 

  142. Li, J., Yang, X., Sitzenfrei, R.: Rethinking the framework of smart water system: a review. Water. 12, 412 (2020)

    Google Scholar 

  143. Gulati, A.: How IoT is playing a key role in protecting the environment. ETTelecom News, June 13 (2017)

    Google Scholar 

  144. Li, S., Wang, H., Xu, T., Zhou, G.: Application study on internet of things in environment protection field. In: Yang, D. (ed.) Informatics in Control, Automation and Robotics. Lecture Notes in Electrical Engineering, vol. 133, pp. 99–106. Springer, Berlin/Heidelberg (2011)

    Google Scholar 

  145. Zhang, X., Huang, Z.: Research on smart environmental protection IoT application based on edge computing. In: 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019). Advances in Computer Science Research, vol. 88, pp. 546–551 (2019)

    Google Scholar 

  146. Ullo, S.L., Sinha, G.R.: Advances in smart environment monitoring systems using IoT and sensors. Sensors. 20, 3113 (2020)

    Google Scholar 

  147. Xu, G., Shi, Y., Sun, X., Shen, W.: Internet of Things in marine environment monitoring: a review. Sensors (Basel). 19(7), 1711 (2019)

    Google Scholar 

  148. Ahmad, T., Chen, H., Guo, Y., Wang, J.: A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: a review. Energ. Buildings. 165, 301–320 (2018)

    Google Scholar 

  149. Frayssinet, L., Merlier, L., Kuznik, F., Hubert, J.-L., Milliez, M., Roux, J.-J.: Modeling the heating and cooling energy demand of urban buildings at city scale. Renew. Sust. Energ. Rev. 81, 2318–2327 (2018)

    Google Scholar 

  150. Tardioli, G., Kerrigan, R., Oates, M., O’Donnell, J., Finn, D.: Data driven approaches for prediction of building energy consumption at urban level. Energy Procedia. 78, 3378–3383 (2015)

    Google Scholar 

  151. Dkhili, N., Eynard, J., Thil, S., Grieu, S.: A survey of modelling and smart management tools for power grids with prolific distributed generation. Sustain. Energ. Grids Netw. 21 (2020)

    Google Scholar 

  152. Naveen, P., Ing, W.K., Danquah, M.K., Sidhu, A.D., Abu-Siada, A.: Cloud computing for energy management in smart grid – an application survey. IOP Conf. Ser.: Mater. Sci. Eng. 121 (2016)

    Google Scholar 

  153. Siano, P.: Demand response and smart grids – a survey. Renew. Sust. Energ. Rev. 30, 461–478 (2014)

    Google Scholar 

  154. Lee, S.W., Sarp, S., Jeon, D.J., Kim, J.H.: Smart water grid: the future water management platform. Desalin. Water Treat. 55, 339–346 (2015)

    Google Scholar 

  155. Yea, Y., Lianga, L., Zhaoa, H., Jianga, Y.: The system architecture of smart water grid for water security. Procedia Eng. 154, 361–368 (2016)

    Google Scholar 

  156. Public Utilities Board Singapore: Managing the water distribution network with a smart Water Grid. Smart Water, 1(4), 13 p. (2016)

    Google Scholar 

  157. Mihăiţă, A.S., Dupont, L., Cheryc, O., Camargo, M., Cai, C.: Evaluating air quality by combining stationary, smart mobile pollution monitoring and data-driven modelling. J. Clean. Prod. 221, 398–418 (2019)

    Google Scholar 

  158. Pule, M., Yahya, A., Chuma, J.: Wireless sensor networks: a survey on monitoring water quality. J. Appl. Res. Technol. 15(6), 562–570 (2017)

    Google Scholar 

  159. Mitchell, L.E., Crosman, E.T., Jacques, A.A., Fasoli, B., Leclair-Marzolf, L., Horel, J., Bowling, D.R., Ehleringer, J.R., Lin, J.C.: Monitoring of greenhouse gases and pollutants across an urban area using a light-rail public transit platform. Atmos. Environ. 187, 9–23 (2018)

    Google Scholar 

  160. Smit, R., Kingston, P., Neale, D.W., Brown, M.K., Verran, B., Nolan, T.: Monitoring on-road air quality and measuring vehicle emissions with remote sensing in an urban area. Atmos. Environ. 218, 116978 (2019)

    Google Scholar 

  161. Kyung, C.-M. (ed.): Smart Sensors for Health and Environment Monitoring. Springer, Dordrecht (2015)

    Google Scholar 

  162. Wei, H., Zheng, G., Gayah, V., Li, Z.: A Survey on Traffic Signal Control Methods. ArXiv, abs/1904.08117. (2019)

    Google Scholar 

  163. Jácome, L., Benavides, L., Jara, D., Riofrio, G., Alvarado, F., Pesantez, M.: A Survey on Intelligent Traffic Lights, 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA), Concepcion, pp. 1–6 (2018)

    Google Scholar 

  164. Soni, A., Hu, H.: Formation control for a fleet of autonomous ground vehicles: a survey. Robotics. 77, 67 (2018)

    Google Scholar 

  165. Zhou, L., Liang, Z., Chou, C.A.: Airline planning and scheduling: models and solution methodologies. Front. Eng. Manag. 7, 1–26 (2020)

    Google Scholar 

  166. Badue, C., et al.: Self-driving cars: a survey. Expert Syst. Appl. 165, 113816 (2021)

    Google Scholar 

  167. Kyriakides, E., Polycarpou., M. (eds.): Intelligent Monitoring, Control, and Security of Critical Infrastructure Systems. Springer Studies in Computational Intelligence, vol. 565. Springer, Berlin/Heidelberg (2015)

    Google Scholar 

  168. Brdys, M.A.: Algorithms and tools for intelligent control of critical infrastructure systems. In: Kyriakides, E., Polycarpou, M. (eds.) Intelligent Monitoring, Control, and Security of Critical Infrastructure Systems. Studies in Computational Intelligence, vol. 565. Springer, Berlin/Heidelberg (2015)

    Google Scholar 

  169. Filip, F.G.: A decision-making perspective for designing and building information systems. Int. J. Comput. Commun. 7(2), 264–272 (2012)

    MathSciNet  Google Scholar 

  170. Zavadskas, E.K., Turskis, Z., Kildienė, S.: State of art surveys of overviews on MCDM/MADM methods. Technol. Econ. Dev. Econ. 20(1), 165–179 (2014)

    Google Scholar 

  171. Rădulescu, C.Z., Rădulescu, I.: An extended TOPSIS approach for ranking cloud service providers. Stud. Inform. Control. 26(2), 183–192 (2017)

    Google Scholar 

  172. Farshidi, S., Jansen, S., de Jong, R., Brinkkemper, S.: A decision support system for software technology selection. J. Decis. Syst. 27(1), 98–110 (2018)

    Google Scholar 

  173. Ani U.P.D., He, H. (M.), Tiwari, A.: Review of cybersecurity issues in industrial critical infrastructure: manufacturing in perspective. J. Cyber Secur. Technol. 1(1), 32–74 (2016). https://doi.org/10.1080/23742917.2016.1252211

  174. Montesino, R., Fenz, S.: Information security automation: how far can we go? In: 2011 Sixth International Conference on Availability, Reliability and Security, pp. 2080–2085. IEEE Computer Society (2011). https://doi.org/10.1109/ARES.2011.48

    Chapter  Google Scholar 

  175. Ogie, R.I.: Cyber security incidents on critical infrastructure and industrial networks. In: ICCAE ‘17: Proceedings of the 9th International Conference on Computer and Automation Engineering, pp. 254–258. ACM, New York (2017)

    Google Scholar 

  176. Yusuf, S., Hong, J.B., Ge, M., Kim, D.S.: Composite Metrics for Network Security Analysis. Cornell University (2020). arXiv:2007.03486v2 [cs.CR]

    Google Scholar 

  177. Fielder, A., Panaousis, E., Malacaria, P., Hankina, C., Smeraldi, F.: Decision support approaches for cyber security investment. Decis. Support. Syst. 86, 13–23 (2016)

    Google Scholar 

  178. Stepanova, T.V., Zegzhda, D.P.: Large-scale systems security evolution: control theory approach. In: Proceedings of the 8th International Conference on Security of Information and Networks (2015). https://doi.org/10.1145/2799979.2799993

    Chapter  Google Scholar 

  179. Kargarian, A., Fu, Y., Li, Z.: Distributed security-constrained unit commitment for large-scale power systems. IEEE Trans. Power Syst. 30(4), 1925–1936 (2015). https://doi.org/10.1109/TPWRS.2014.2360063

    Article  Google Scholar 

  180. Liu, C., Shahidehpour, M., Fu, Y., Li, Z.: Security-constrained unit commitment with natural gas transmission constraints power systems. IEEE Trans. 24(3), 1523–1536 (2009)

    Google Scholar 

  181. Hart, W.E., Murray, R.: Review of sensor placement strategies for contamination warning systems in drinking water distribution systems. J. Water Resour. Plan. Manag. 136(6), 611–619 (2010)

    Google Scholar 

  182. Laracy, J.: A systems-theoretic security model for large scale complex systems applied to the US air transportation system. Int. J. Commun. Netw. Syst. Sci. 10, 75–105 (2017). https://doi.org/10.4236/ijcns.2017.105005

    Article  Google Scholar 

  183. Chowdhury, N., Gkioulos, V.: Cyber security training for critical infrastructure protection: a literature review. Comput. Sci. Rev. 40, 100361 (2021)

    Google Scholar 

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Authors and Affiliations

  1. The Romanian Academy, Bucharest, Romania

    Florin Gheorghe Filip

  2. Control Engineering Laboratory, University of Oulu, Oulu, Finland

    Kauko Leiviskä

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  1. Florin Gheorghe Filip
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  2. Kauko Leiviskä
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Correspondence to Florin Gheorghe Filip .

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  1. PRISM Center and School of Industrial Engineering, Purdue University, West Lafayette, IN, USA

    Shimon Y. Nof

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Filip, F.G., Leiviskä, K. (2023). Infrastructure and Complex Systems Automation. In: Nof, S.Y. (eds) Springer Handbook of Automation. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-030-96729-1_27

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