Navigating Applied Artificial Intelligence (AI) in the Digital Era: How Smart Buildings and Smart Cities Become the Key to Sustainability
DOI:
https://doi.org/10.47852/bonviewAIA32021063Keywords:
construction, CDR, digitization, BIM, AI, digital twins, smart citiesAbstract
This paper aims to understand the critical path of digital transformation in construction by investigating major drivers for technical innovation, e.g., in smart cities. Despite available new technologies, increasing societal, environmental pressure, and data complexity, the branch lacks a will to innovate and qualified personnel. The study identifies the potential of innovation and the pillars of sustainability to define ways to responsibly use data-driven, smart technologies in smart cities throughout their holistic life cycles. The mix of expert interview surveys and structured literature analysis is the basis to examine the status quo and innovative approaches. It enables to critically investigate limitations and human, societal and environmental impacts. This study’s findings offer orientation in navigating innovation for resilient, agile ecosystems with the dynamic ability to adapt to changing environment and to grow with the change and achieving the sustainable development goals toward preservation and upgrade of buildings instead of new construction. The key challenge for sustainable technical innovation is to exploit human and societal potential. The study allocates the lack of research in this field and inadequate education as most significant limitations and critically evaluates that a disruptive culture of thinking may enable the sustainable design of smart cities. This study is unique as it develops a comprehensive, transparent Corporate Digital Responsibility Policy Framework and provides orientation to assume ethical, societal, environmental responsibility as part of creating resilient, agile environments.
Received: 11 May 2023 | Revised: 14 July 2023 | Accepted: 25 July 2023
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.
Data Availability Statement
Data available on request from the corresponding author upon reasonable request.
Author Contribution Statement
Bianca Weber-Lewerenz: Conceptualization, Methodology, Validation, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration. Marzia Traverso: Writing - review & editing, Supervision.
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Copyright (c) 2023 Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.