Incremental transformation of spatial intelligence from smart systems to sensorial infrastructures


Erişen S.

Building Research and Information, cilt.49, sa.1, ss.113-126, 2021 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49 Sayı: 1
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1080/09613218.2020.1794778
  • Dergi Adı: Building Research and Information
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, PASCAL, Aerospace Database, Art Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, ICONDA Bibliographic, Index Islamicus, INSPEC, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.113-126
  • Anahtar Kelimeler: embedded computation and smart grids, learning, Performance assessment, policy measures, technological performance, urban informatics and computing
  • Hacettepe Üniversitesi Adresli: Hayır

Özet

In addition to the scalability of new computation technologies considering their potentials and limitations, recent applications of embedded computation ensure its possible uses in the scope of urban computing and policymaking strategies. This study examines methods of crowdsourcing with the aim of incremental transformation of the built environment through the experimental exploration of the traditional infrastructure of the Spice Bazaar in İstanbul using a bottom-up research approach. Thus, this study can be an overarching source of specifications and policymaking for the incremental transformation of the built environment. Accordingly, the agencies of participation and policymaking, the concern of usage and economics as well as technological potentials and limitations are considered as generative parameters. Smart grids and embedded computation in built environments are examined in addition to the utilization of traditional infrastructures for data acquisition and assessment. Under the scope of urban computing, this study evaluates associative learning and prediction models, as well as other sensorial technologies, connected devices, and new methods of computation.