847
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Incremental transformation of spatial intelligence from smart systems to sensorial infrastructures

ORCID Icon
Pages 113-126 | Received 28 Mar 2020, Accepted 07 Jul 2020, Published online: 24 Jul 2020

References

  • Andreev, S., Dobre, C., & Misra, P. (2020). Internet of Things and sensor networks. IEEE Communications Magazine, 58(2), 34. https://doi.org/10.1109/MCOM.2020.8999424
  • Arbib, M. A. (2012). Brains, machines and buildings: Towards a neuromorphic architecture. Intelligent Buildings International, 4(3), 147–168. https://doi.org/10.1080/17508975.2012.702863.
  • Barjatya, A. (2011). Block matching algorithms for motion estimation. https://www.mathworks.com/matlabcentral/fileexchange/8761-block-matching-algorithms-for-motion-estimation
  • Batty, M. (2011). The new science of cities. The MIT Press.
  • Batty, M. (2012). A generic framework for computational spatial modelling. In A. Heppenstall, A. Crooks, L. See, & M. Batty (Eds.), Agent-based models of geographical systems (pp. 19–50). Springer.
  • Batty, M. (2018). Digital twins. Environment and Planning B: Urban Analytics and City Science, 45(5), 817–820. https://doi.org/10.1177/2399808318796416
  • Berman, J. J. (2018). Principles and practice of big data: Preparing, sharing, and analyzing complex information. Academic Press.
  • Beyea, W., Geith, C., & McKeown, C. (2009). Place making through participatory planning. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 55–67). IGI Global.
  • Bhattacharya, A., Metcalf, A. R., Nafchi, A. M., & Mousavi, E. S. (2020). Particle dispersion in a cleanroom – effects of pressurization, door opening and traffic flow. Building Research & Information, 47(5), 1–15. https://doi.org/10.1080/09613218.2020.1720500
  • Bouhai, N., & Saleh, I. (2017). Internet of Things. Evolutions and innovations. ISTE; John Wiley & Sons.
  • Bressani, M. (2013). On the surface: Notes toward an architecture of affect. In P. Lorenzo-Eiroa, A. Sprecher, P. Lorenzo-Eiroa, & A. Sprecher (Eds.), Architecture in formation (pp. 323–329). Routledge.
  • Calabrese, F., Kloeckl, K., & Ratti, C. (2009). Wikicity: Real-time location-sensitive tools for the city. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 390–413). IGI Global.
  • Claypool, M., Garcia, M. J., Retsin, G., & Soler, V. (Eds.). (2019). Robotic building. Architecture in the age of automation. Detail.
  • Courtland, R. (2018, June). Bias detectives: The researchers striving to make algorithms fair. Nature, 558(7710), 357–360. https://doi.org/10.1038/d41586-018-05469-3
  • Davies, M., Srinivasa, N., Lin, T. H., Chinya, G., Cao, Y., Choday, S. H., Dimou, G., Joshi, P., Imam, N., Jain, S., & Liao, Y. (2018, January/February). Loihi: A neuromorphic manycore processor with on-chip learning. IEEE Micro, 38(1), 82–99. https://doi.org/10.1109/MM.2018.112130359
  • Ding, M., Zhou, Z., Traferro, S., Liu, Y.-H., Bachmann, C., & Sebastiano, F. (2020). A 33-ppm/°C 240-nW 40-nm CMOS wakeup timer based on a bang-bang digital intensive frequency-locked-loop for IoT applications. IEEE Transactions on Circuits and Systems I: Regular Papers, 1–11. https://doi.org/10.1109/TCSI.2020.2979319
  • Eicker, U., Weiler, V., Schumacher, J., & Braun, R. (2020). On the design of an urban data and modeling platform and its application to urban district analyses. Energy and Buildings, 217, 109954. https://doi.org/10.1016/j.enbuild.2020.109954.
  • Emmitt, S. (2013). Research processes and practicalities. In S. Emmitt (Ed.), Architectural technology. Research & practice (pp. 231–246). Wiley-Blackwell.
  • Emmitt, S. (2019). Living with buildings. Building Research & Information, 47(7), 785–786. https://doi.org/10.1080/09613218.2019.1637595
  • Erişen, S. (2018). Archi-learn online. In Digital Transformation & Smart Systems 2018, Conference Proceedings. (pp. 141–144). ODTÜ-BİLTİR.
  • Forlano, L. (2009). Codespaces: Community wireless networks and the reconfiguration of cities. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 292–309). IGI Global.
  • Fox, M., & Kemp, M. (2009). Interactive architecture. Princeton Architectural Press.
  • Geng, H. (2017). Internet of Things and data analytics handbook. John Wiley & Sons.
  • Gibney, E. (2020). The battle for ethical AI at the world's biggest machine-learning conference. Nature, 577(7792), 609. https://doi.org/10.1038/d41586-020-00160-y
  • Gonzalez, V., Kraemer, K., & Castro, L. (2009). Beyond safety concerns: On the practical applications of urban neighborhood video cameras. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 131–143). IGI Global.
  • Hartley, C., Moscarello, J. M., Quirk, G. J., & Phelps, E. (2014). The cognitive neuroscience of fear and its control: From animal models to human experience. In M. S. Gazzaniga & G. R. Mangun (Eds.), The cognitive neurosciences (pp. 697–708). The MIT Press.
  • Hassanien, A. E., Azar, A. T., Snasel, V., Kacprzyk, J., & Abawajy, J. H. (2015). Big data in complex systems: Challenges and opportunities. Springer.
  • Hassanien, A. E., & Emary, E. (2016). Swarm intelligence: Principles, advances, and applications ( A. E. Emary Ed.). CRC Press.
  • Hebb, D. O. (1949). The organization of behavior: A neurophysiological theory. Wiley.
  • Hudson-Smith, A., Milton, R., Dearden, J., & Batty, M. (2009). The neogeography of virtual cities: Digital mirrors into a recursive world. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 270–291). IGI Global.
  • Jeon, M. (2017). Emotions and Affect in human factors and human-computer interaction. Elsevier.
  • Klaebe, H., Adkins, B., Foth, M., & Hearn, G. (2009). Embedding an ecology notion in the social production of urban space. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 179–195). IGI Global.
  • Kocatürk, T. (2017). Towards an intelligent digital ecosystem – sustainable data-driven design Futures. In P. Brandon, P. Lombardi, & G. O. Shen (Eds.), Future challenges in evaluating and management sustainable development in the built environment (pp. 164–178). John Wiley & Sons.
  • Kocatürk, T. (2019). Intelligent building paradigm and data-driven models of innovation. Architectural Engineering and Design Management, 15(5), 1–2. https://doi.org/10.1080/17452007.2019.1649284
  • Konsoulas, I. (2015). Dynamic, recurrent fuzzy neural network (RFNN) library for simulink. Mathworks File Exchange. https://www.mathworks.com/matlabcentral/fileexchange/43021-recurrent-fuzzy-neural-network-rfnn-library-for-simulink
  • Krutov, D. (2018). Dense associative memories and deep learning. YouTube: https://www.youtube.com/watch?v=lvuAU_3t134
  • Kunita, I., Yoshihara, K., Tero, A., Ito, K., Lee, C. F., Fricker, M. D., & Nakagaki, T. (2013). Adaptive path-finding and transport network formation by the Amoeba-like organism physarum. In Y. Suzuki & T. Nakagaki (Eds.), Natural computing and beyond (pp. 14–29). Springer.
  • Latour, B. (2005). Reassembling the social. An introduction to actor-network-theory. Oxford University Press.
  • Lehman, M. L. (2017). Adaptive sensory environments. Routledge.
  • Li, T., Fong, S., Millham, R. C., Fiaidhi, J., & Mohammed, S. (2019, March). Fast incremental learning with swarm decision table and stochastic feature selection in an IoT extreme automation environment. IT Professional, 21(2), 14–26. https://doi.org/10.1109/MITP.2019.2900016
  • Liberg, O. (2018). Cellular Internet of Things: Technologies, standards, and performance. Academic Press.
  • McElroy, D., & Rosenow, J. (2019). Policy implications for the performance gap of low-carbon building technologies. Building Research & Information, 47(5), 611–623. https://doi.org/10.1080/09613218.2018.1469285
  • Mitchell, W. J. (2003). Me++. The cyborg self and the networked city. MIT Press.
  • Nakanishi, H., Ishida, T., & Koizumi, S. (2009). Virtual cities for simulating smart urban spaces. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 257–269). IGI Global.
  • Ng, A. (2017). Online learning. https://www.coursera.org/learn/machine-learning/lecture/ABO2q/online-learning
  • Nielsen, M. A., & Chuang, I. L. (2010). Quantum computation and quantum information. Cambridge University Press. (Original work published 2000).
  • Özkan, A., Kesik, T., Yilmaz, A., & O’Brien, W. (2019). Development and visualization of time-based building energy performance metrics. Building Research & Information, 47(5), 493–517. https://doi.org/10.1080/09613218.2018.1451959
  • Park, S. (1998). Neural networks and psychopharmacology. In D. J. Stein & J. Ludik (Eds.), Neural networks & psychopathology. Connectionist models in practice and research (pp. 57–87). Cambridge University Press.
  • Paulos, E., Honicky, R., & Hooker, B. (2009). Citizen science: Enabling participatory urbanism. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 414–436). IGI Global.
  • Picard, R. W. (2000). Affective computing. The MIT Press.
  • Picon, A. (2015). Smart cities. A spatialized intelligence. John Wiley & Sons.
  • Sevtsuk, A., Huang, S., Calabrese, F., & Ratti, C. (2009). Mapping the MIT campus in real-time using WiFi. In M. Foth (Ed.), Handbook of research on urban informatics: The practice and promise of the real-time city (pp. 326–338). IGI Global.
  • Smale, R., Spaargaren, G., & van Vliet, B. (2019). Householders co-managing energy systems: Space for collaboration? Building Research & Information, 47(5), 585–597. https://doi.org/10.1080/09613218.2019.1540548
  • Suzuki, Y., & Nakagaki, T. (2013). Natural computing and beyond. Springer.
  • Tait, A., Nahmias, M., Tian, Y., Shastri, B., & Prucnal, P. (2014). Photonic neuromorphic signal processing and computing. In M. Naruse (Ed.), Nanophotonic information physics. Nano-optics and nanophotonics (pp. 183–222). Springer.
  • Tsiatsis, V., Karnouskos, S., Höller, J., Boyle, D., & Mulligan, C. (2019). Internet of Things: Technologies and applications for a new age of intelligence. Elsevier.
  • Zheng, Y. (2018). Urban computing. The MIT Press.
  • Zheng, Y., Carpa, L., Wolfson, O., & Yang, H. (2014). Urban computing: Concepts, mehodologies, and applications. ACM Transactions on Intelligent Systems and Technology, 5(3), 1–55. https://doi.org/10.1145/2629592

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.