Open Access
E3S Web Conf.
Volume 111, 2019
CLIMA 2019 Congress
Article Number 05004
Number of page(s) 8
Section Information and Communication Technologies (ICT) for the Intelligent Building Management
Published online 13 August 2019
  1. Oxford Dictionaries. Internet of Things Definition. (2018) [cited 2019 Jan.] [Google Scholar]
  2. M. Ernst. IoT For Smart Buildings Isn’t What You Think It Is., (2018) [cited 2018 Dec.] [Google Scholar]
  3. B.S. Brad and M.M. Murar, Smart Buildings using IoT Technologies. Construction of Unique Buildings and Structures. 5(20): p. 15–27, (2014) [Google Scholar]
  4. J. Petze. Using Data to Improve Facility Operations., (2017) [cited 2018 Dec ] [Google Scholar]
  5. T. Kannegieter. The IoT and Building Management, (2018) [Google Scholar]
  6. S. Caluianu and F.A. Hebean, Cloud Computing and Internet of Things Concepts applied on Buildings Data Analysis. Mathematical Modelling in Civil Engineering. 13(4): p. 39–49, (2017) [CrossRef] [Google Scholar]
  7. S. Soursos, et al., Towards the cross-domain interoperability of IoT platforms, in EU Conf. on Networks and Communications (EuCNC) Athens, Greece. p. 398-402, (2016). [Google Scholar]
  8. O. Noran and M. Zdravković, Interoperability as a Property: Enabling an Agile Disaster Management Approach, in ICIST 2014: Kopaonik, Serbia, (2014) [Google Scholar]
  9. Q. Chi, et al., A Reconfigurable Smart Sensor Interface for Industrial WSN in IoT Environment. IEEE Trans Ind. Inf, 10(2): p. 1417–1425, (2014) [CrossRef] [Google Scholar]
  10. D. Sikeridis, et al., Socio-Physical Energy-Efficient Operation in the Internet of Multipurpose Things, in 2018 IEEE Int’l Conference on Communications (ICC): Kansas City, MO. p. 1-7, (2018). [Google Scholar]
  11. M. Manic, et al., Building Energy Management Systems: The Age of Intelligent and Adaptive Building. IEEE Industrial Electronics Magazine. 10(1): p. 25–39, (2016) [Google Scholar]
  12. J. Ploennigs, A. Ba, and M. Barry, Materializing the Promises of Cognitive IoT: How Cognitive Buildings are Shaping the Way. IEEE Internet of Things J. 5(4): p. 2367–2374, (2018) [CrossRef] [Google Scholar]
  13. J. Fürst, et al., Crowd-sourced BMS Point Matching and Metadata Maintenance with Babel, in PerCom Workshops. p. 1-6, (2016). [Google Scholar]
  14. N. Suh, Complexity: Theory and Applications. Oxford University Press, (2005). [Google Scholar]
  15. I. Gorzeń-Mitka and M. Okręglicka, Managing Complexity: Current Strategies and Approaches .Procedia Econ & Fin. 27: p. 438–444, (2015) [CrossRef] [Google Scholar]
  16. O.L. de Weck, Life-Cycle Properties of Engineering Systems: The Ilities, in En. Sys., O. de Weck, D. Roos, and C. Magee, (Eds.). p. 65-96, (2011). [Google Scholar]
  17. J.R. Rabelo, O. Noran, and P. Bernus, Towards the Next Gen Service Oriented Enterprise Architecture, in Proc. IEEE 19th Int. Enterprise Distributed Object Computing Workshop. p. 91-100, (2015). [Google Scholar]
  18. R.J. Rabelo, P. Bernus, and D. Romero, Innovation Ecosystems: A Collaborative Networks Perspective .Risks and Resilience of Collaborative Networks. IFIP AICT 463: p. 323–336, (2015) [CrossRef] [Google Scholar]
  19. S. Beer, Brain of the firm. London: Allan Lane Penguin Press, (1972). [Google Scholar]
  20. P. Hoverstadt, The Fractal Organization: Creating sustainable organizations with the Viable System Model. Hoboken, N.J.: Wiley, (2008). [Google Scholar]
  21. P. Turner, P. Bernus, and O. Noran, Enterprise Thinking for Self-aware Systems .IFAC Papers OnLine. 51(11): p. 782–289, (2018) [Google Scholar]
  22. O. Noran and P. Bernus, Business Cloudification: An Enterprise Architecture Perspective. , in Procs of ICEIS2017 J. Filipe, et al., (Eds.). ScitePress: Porto, Portugal. p. 353-360, (2017). [Google Scholar]
  23. G. Doumeingts, B. Vallespir, and D. Chen, GRAI Grid Decisional Modelling, in Handbook on Architectures of IS P. Bernus, K. Mertins, and G. Schmidt, (Eds.). Springer Verl.: p. 313-339, (1998). [Google Scholar]
  24. T. Olavsrud. 11 Steps Attackers Took to Crack Target. /security0/11-steps-attackers-took-tocrack-target.html, (2014) [cited 2019 Jan] [Google Scholar]
  25. K. Zetter. Researchers Hack Building Control System at Google Australia Office., (2013) [cited 2018 Dec] [Google Scholar]
  26. K. Paridari, et al. Cyber-Physical-Security Framework for Building Energy Management System. in 2016 ACM/IEEE 7th (ICCPS). (2016). [Google Scholar]
  27. C. Grundy, Cybersecurity in the built environment: Can your building be hacked? Corporate Real Estate Journal. 7(1): p. 39–50, (2017) [Google Scholar]
  28. K.J. Devlin, Logic and Information. Cambridge University Press, (1995). [Google Scholar]
  29. T. Goranson and B. Cardier, A two-sorted logic for structurally modelling systems .Progress in Biophysics / Molecular Bio. 113: p. 141–178, (2013) [CrossRef] [Google Scholar]
  30. P. Bernus and O. Noran, Data Rich – But Information Poor .IFIP Advances in ICT. 506: p. 206–214, (2017) [Google Scholar]
  31. M. Hirzalla, Realizing Business Agility Requirements through SOA and Cloud Computing, in 18th IEEE Int’l Req Eng Conf. p. 379-380, (2010). [Google Scholar]
  32. M. Sawas and M. Watfa, The impact of cloud computing on information systems agility .Australasian J of Info. Sys. 19: p. 97–112, (2015) [Google Scholar]
  33. F. Liu, et al., NIST Cloud Computing Reference Architecture. NIST SP 500-292. , Gaithersburg, MD: NIST IT Laboratory, (2011). [Google Scholar]
  34. E. Cayirci, et al., A risk assessment model for selecting Cloud Service Providers .J. Cloud Computing. 5(14), (2016) [CrossRef] [Google Scholar]
  35. W. Jansen and T. Grance, Guidelines on security and privacy in public cloud computing .NIST special publication 800-144. (2011) [Google Scholar]
  36. M. Morrow, et al., Blueprint for the Intercloud - Protocols and Formats for Cloud Computing Interoperability, in Int’l Conference on Internet and Web Applications and Services. p. 328-336, (2009). [Google Scholar]
  37. F. Aulkemeier, et al., A pluggable service platform architecture for e-commerce .J. Inf Syst E-Bus Management. 14: p. 469–489, (2016) [CrossRef] [Google Scholar]
  38. G. Laatikainen, A. Ojala, and O. Mazhelis, Cloud Services Pricing Models, in Software Business. G. Herzwurm and T. Margaria, (Eds.). Springer: Berlin Heidelberg, (2013). [Google Scholar]
  39. S. Zardari, F. Faniyi, and R. Bahsoon, Using obstacles for systematically modeling, analysing, and mitigating risks in cloud adoption, in Aligning Ent. Sys. & Sw Arch. IGI Global. p. 275-296, (2012). [Google Scholar]
  40. L. Chen, M. Ali Babar, and B. Nuseibeh, Characterizing Architecturally Significant Requirements. IEEE S’ware. 30(2): p. 38–45, (2013) [Google Scholar]
  41. J. Gao, J. Ploennigs, and M. Berges, A data-driven meta-data inference framework for building automation systems”, in BuildSys - 2nd ACM Conf. on Embedded Sensing Systems. .. p. 23-32, (2015). [Google Scholar]
  42. F. Osinga, Science, strategy and war: The strategic theory John Boyd. , London, UK: Routledge, (2006). [Google Scholar]
  43. K. Benson and S. Rotkoff, Goodbye, OODA loop: A complex world demands a different kind of decision-making. Armed Forces J. 149(3): p. 26–28, (2011) [Google Scholar]
  44. B. Marr, Big Data: Using Smart Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance Wiley & Sons, (2015). [Google Scholar]
  45. R. Corrigan, Digital Decision Making: Back to the Future. Springer Verlag, (2007). [Google Scholar]
  46. O. Noran and P. Bernus, Improving Digital Decision Making Through Situational Awareness. , in Info. Systems Development: Designing Digitalization B. Andersson, et al., (Eds.): Lund. Sweden, (2018). [Google Scholar]
  47. D.S. Fadok, J. Boyd, and J. Warden, Air Power’s Quest for Strategic Paralysis, ed. Maxwell Air Force Base AL. Air University Press, (1995). [Google Scholar]
  48. V. Lenders, A. Tanner, and A. Blarer, Gaining an Edge in Cyberspace with Advanced Situational Awareness .IEEE Sec & Priv 13(2): p. 65–74, (2015) [Google Scholar]
  49. M. Li, et al., Big Data-driven Technology Innovation: Concept and Key Problems, in Procs of WHICEB 2017. AIS Electronic Library, (2017). [Google Scholar]

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