In addressing the intricate labyrinth of today's urban challenges, it becomes evident that traditional diagnostic tools have reached their limitations. The city, with its myriad layers, pulses, and rhythms, cannot be discerned merely through static metrics or one-dimensional measures such as carbon footprints. The rapid pace and transient nature of urban flows demand a continuous, real-time diagnostic approach. [1]

Current urban diagnostics, compared to medical practices, resemble a cursory skin check. Such superficial examinations, focusing solely on a city's visible exterior, fail to capture the dynamic interplay of its internal flows and mechanisms. [2] It neglects the essence of the city as a multifaceted living organism, thriving and evolving through its interwoven systems.[3] Analogous to the medical world, where a physician employs an array of diagnostic tools—from X-rays to blood tests, from CT scans to genetic profiling—to holistically understand the human body, urban diagnostics necessitates similar “deeper” tools.

The Blue City project seeks to revolutionize city diagnosis. Venturing beyond traditional mapping and indexing, which only capture the city's skeletal framework, the project dives deep into the city's vascular systems. It investigates utilities and infrastructures, the conduits that sustain urban life, and examines the city's pulsating flow—of human capital, of goods and services, of knowledge and culture. It assesses the city's metabolic rate, gauging both its resource consumption and waste production, offering a comprehensive urban health check.

Combining generative AI and spatial analytics into “generative spatial AI,” Blue City addresses the critical challenges in city diagnosis on an unprecedented scale.[4] Through generative spatial AI, gaps in city data can be impartially completed, urban flows in new and previously inaccessible locations estimated, and the trajectories of these flows predicted, as they shape the future urban landscape.

[1] Virilio, P. (1999). Polar Inertia. Sage.

[2] Batty, M. (2013). The New Science of Cities. MIT Press.

[3] Portugali, J. (2011). Complexity, Cognition and the City. Springer.

[4] Huang, J., and Keel, P., (2023). Generative Spatial AI. White Paper. http://generativespatialai.com.