The combination of artificial intelligence (AI) and urban planning offers great potential for the creation of smarter, more efficient, and sustainable cities. This merging involves incorporating state-of-the-art technologies that can assist in decision-making, : optimize resource allocation, forecast trends, engage with citizens, and much more. Within this context, where AI Blueprint is regarded as a tool for advancing different urban facets, there has been a notable increase in the creation of applications, software, and other technological systems specifically designed to aid urban planning. Here, we present a selection of global studies and technologies that range from urban morphology to community participation.
Cityscape Crafting: Exploring Urban Design and Morphology:
The notion of the “creator being surpassed by the creation” has never been more evident than in the realm of urban design and artificial intelligence. A group of urban planners and scientists from Tsinghua University in China have recently developed an AI-driven urban planning system that surpasses the capabilities of human urban planners in project creation. Their findings, published in the journal Nature Computational Science, delve into the factors utilized to define the optimal urban plan within the framework of the “15-minute city” concept. By training the system with past human-designed projects and incorporating positive attributes such as parks, bike lanes, and recreational spaces, the researchers were able to demonstrate that the plans generated by the AI system were on par with, if not superior to, those crafted by experts. Remarkably, all of this was accomplished in a matter of seconds.
Digital Blue Foam, a technology company headquartered in Singapore, has recently launched Urban Insights, a cutting-edge tool designed for swift urban prototyping. By aggregating data from multiple open sources, this innovative tool empowers project teams to create urban scenarios and evaluate the merits of different locations. To ensure a comprehensive and scientific analysis of the projects, DBF collaborates with renowned experts like Carlos Moreno, the visionary behind the “15-minute city” concept, as well as esteemed institutions such as the Bern University of Applied Sciences.
As previously mentioned, the utilization of urban prototyping for the examination of various compositions and strategies is a highly promising application of AI in urban planning. Within this context, it is crucial to emphasize the significance of “digital twins” technology. This AI tool encompasses three key elements: visualization, prediction, and diagnosis. It offers the opportunity to digitally simulate and test alterations to the urban landscape prior to their actual implementation, enabling the anticipation of how modifications to one structure may impact its surroundings. This meticulous approach to urban planning prevents stagnation and ensures continuous progress for the city. Notable examples of this practical implementation include BuildMedia, which is currently developing a digital twin of Wellington, New Zealand, and the Chinese company 51World, which has successfully created a digital twin of Shanghai.
Urban planning:Resilience and Climate Adaptation
AI has the potential to support cities in addressing the challenges posed by climate change. By utilizing predictive modeling, risk assessment, and early warning systems driven by AI, cities can strengthen their ability to withstand and respond to extreme weather events.
An example of this is Google’s Tree Canopy, which utilizes artificial intelligence to assist in urban planning and minimize the effects of intense heat waves. This tool is integrated into Google’s Environmental Insights Explorer and utilizes aerial images of cities, combined with AI technology. By doing so, it enables governments to gain insights into the extent of tree coverage and facilitates more efficient planning for the establishment of new tree plantations.
Furthermore, it is important to highlight the efforts of IBM researchers who have devised a method to precisely detect, chart, and quantify the carbon storage capacity of trees in a designated region. This study considers various factors such as the species of trees, their geometric structure, and the volume of their foliage. As an illustration, the researchers were able to determine that trees in Manhattan are capable of retaining 52 thousand tons of carbon, thereby identifying the specific attributes that contribute to the efficacy of certain tree species and the optimal locations for different types of trees. This knowledge facilitates the successful integration of vegetation in urban areas, enhancing their overall sustainability.
Development Strategy: Exploring Infrastructure Planning:
Aerial mapping, as demonstrated in the previous example, offers crucial data to enhance different urban aspects, making it a valuable resource for data analysis.
In 2021, Colombia’s National Planning Department (DNP) introduced an innovative pilot project that combines aerial mapping with urban diagnostics to tackle the issue of informal settlements in the country. The project discovered that around 85% of the areas identified by algorithmic maps coincided with those verified and outlined by local experts. This high level of accuracy proved sufficient to identify and prioritize areas in need of public policies for spatial improvement. Building upon the promising outcomes of the initial project, the MAIIA software (Automated Mapping of Informal Settlements with Artificial Intelligence) was developed. MAIIA is a component of the Open Urban Planning Toolbox, a collection of open-source digital tools for urban planning. The objective is to streamline the automated detection and mapping of informal settlements in various locations, offering efficient and accessible solutions to housing challenges.
Community Involvement: Fostering Collaboration and Participation:
AI-powered tools have the potential to improve communication between urban planners and the community. By utilizing virtual reality (VR) or augmented reality (AR), residents can better visualize proposed changes and provide valuable feedback, resulting in a more inclusive planning process.
Furthermore, AI initiatives are being implemented to enhance the monitoring and analysis of data, particularly in mobility-related matters such as intelligent traffic management, traffic light control, and camera surveillance. These initiatives also leverage user-generated data to identify safe routes and monitor public spaces for potential threats to pedestrian safety. Additionally, there are specific applications focused on urban safety for women that utilize artificial intelligence to gather user information and determine the safety level of a particular route.
In the realm of urban planning, a complex and ever-evolving field, the use of artificial intelligence (AI) has gained attention as a potential solution to various challenges. However, before AI can be seamlessly integrated into urban planning, there are obstacles that need to be overcome. One major challenge is the limited availability of data. The effective application of AI in urban planning relies on accurate and comprehensive data, which includes factors such as population density, traffic flow, and land use. However, obtaining such data can be difficult due to privacy concerns or incomplete datasets.
While AI grapples with the issue of data scarcity, there has been much discussion about the role of citizens, often referred to as the “unpaid data providers.” This raises questions about a scenario where we willingly provide information for an urban database, which is often exploited for profit by private companies. Despite the successes and contradictions surrounding this topic, it is undeniable that AI has immense potential when combined with urban planning. This is an avenue that should be further explored. However, it is crucial to recognize the importance of collaboration among urban planners, policymakers, technologists, and the community to ensure that AI solutions are implemented responsibly and inclusively.