Convergence evolution explains how different species evolve
with similar traits. Technology is perhaps the unifying element that brings all cities to a similar level of enablement and operational control.

Smart Cities and Artificial Intelligence offers a comprehensive view of how cities are evolving as smart ecosystems through the convergence of technologies incorporating machine learning and neural network capabilities, geospatial intelligence, data analytics and visualization, sensors, and smart connected objects.
“Designing cities as biomimetic, self-regulating ecosystems augmented by artificial intelligence, machine learning and blockchain, smart cities can monitor human patterns in real-time, enabling the rebalancing of the environment and the operations of the city.”
Today cities behave more like living systems—breathing, sensing, adapting, and learning.

As the first chapter in this comprehensive anthology, we describe the future direction of cities as autonomous, self-regulating, biomimetic systems based on principles in nature and evolution itself.

Operating system typologies relating all elements within the living system from Macro to Micro.

Urban OS as the convergence of human user experience, physical infrastructure and software applications.

New forms of communication emerging between human, nature and machine intelligence.

Smart connected objects imbedded within diverse scales and environments from buildings to people to nano objects.




Smart Cities Project Portfolio
Smart City DNA Analysis
Newark Aeroportropolis Masterplan
The Ecosphere - Utapao Airport Masterplam
Buffalo GIS Mapping and Urban Metrics

Smart Park Riyadh
Harrison Town Square Smart Community

Montclair Integrated Urban Media Interface
Newark Integrated Urban Media Interface

The Point Smart City, Utah

The City as Urban Media Interface

Beijing Interactive Map
Tsinghua University with Ars Electronica