An AIoT-driven UDT framework for data-driven environmental planning in sustainable smart cities.
Bibri, Simon Elias, et al. "The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: a comprehensive systematic review." Environmental Science and Ecotechnology (2024): 100433.

Ethical frameworks for urban digital twins

By integrating the deployment of AI and internet of things networks for sensing and control, Urban digital twins (UDT) have the potential to enhance data-driven environmental planning. However, a review of 185 UDT studies from 2019 to 2023 finds that the lack of a comprehensive framework addressing "privacy and security concerns, ethical and social issues, lack of data interoperability, environmental risks, financial constraints, regulatory inadequacies, lack of community engagement, and stakeholder conflicts" is holding back the development of these tools. A number of strategies are identified, including "implementing robust privacy and security measures for data protection, addressing ethical and social concerns through transparent and inclusive decision-making processes, developing standardization protocols and frameworks, sustainable technology and eco-design practices, securing funding and resources, and devising sustainable funding schemes, advocating for robust data governance frameworks that support innovation while safeguarding public interests, and facilitating stakeholder collaboration and conflict resolution through effective communication and engagement and capacity-building endeavors."

As owners and stakeholders of urban digital twins develop and implement strategies for addressing the socio-technical concerns of these systems, their use in climate resilience and adaptation planning with become more effective and trusted, augmenting cities' ability to exploit data-driven urban planning informed by real-time monitoring and predictive analytics.

Source: sciencedirect.com
Sector
Building Systems
Other Systems
Tags
digital twin
planning
sustainability
AI
iot
planning technology