By Orkan Telhan and Dietmar Offenhuber
This is the description of our contribution to the Biennale Architecture 2025 in Venice. The installation demonstrates ecological urban computing involving autographic principles.
The installation was realized with the help of Jesus Ocampo Aguilar, Paula Martin Rivero, Sebastian Gonzalez Quintero, Joel Murphy, Österreichisches Bundesministerium für Kunst, Kultur, öffentlicher Dienst und Sport, the
College of Arts Media and Design, Northeastern University, MAI International GmbH and the @iloveyouvenice youtube webcam channel
The project examines the city as a medium of information processing, using its physical phenomena to capture and predict the city’s changing environmental conditions. The title refers to the emerging field of physical reservoir computing, which explores the potential of physical processes to build self-learning systems. The installation presents a city-wide reservoir computing model in which Venice serves as a data source and computing agent who makes predictions about its future.
Reservoirs of Venice is a critical contribution to the urban computing discourse, aiming to expand the field beyond its data-centric focus and draw attention to the layers of meaning inherent in the environment. Urban computing can be broadly divided into two distinct approaches; we propose a third paradigm:
Ecological Urban Computing
The current paradigm uses sensors, control systems, and data streams to model, predict, and control urban processes. The focus is often on human behavior and movement, which raises widespread concerns about surveillance. At the core of this paradigm are data as epistemological artifacts that represent the material and social realities of the city as digital abstractions.
A second approach avoids abstraction and representation, focusing instead on analog information derived from physical processes. These processes can either be applied as analogies (e.g., using slime mold to model road networks) or used as indicators of hidden processes. Pursued by a historical branch of cybernetics, this approach rejected the concept of symbolic data and instead emphasized relations, interactions, and causal effects.
In our project, we engage with a third emerging paradigm. Here, physical processes serve as computational substance-not as analogies to existing problems, but as foundations for alternative models of information processing beyond Turing machines and von Neumann architectures. Dynamic, nonlinear processes become the basis for learning systems embedded in our environment.
This approach challenges existing notions of information, data, computing, and machine learning. In our ecological approach to urban computing, multiple computational processes are layered across different stakeholders – the built environment, biological actors, or the climate. Our “reservoir computer” interprets human activity observed from bridges, captured by vibrations, sounds, and reflections from passing boats, and predicts the time of day based on the intensity of these signals. Unlike energy-intensive digital AI systems, this computer is composed of the very elements it uses to compute, and requires only a fraction of the energy to operate.
In an era increasingly characterized by digital mediation and artificial intelligence, the project serves as a reminder that the urban environment processes information and documents it through countless traces. Our project seeks to foster a new sensibility towards the city as a collective entity, to develop a new understanding of its intelligence that goes beyond digital means. Imagine if the city could predict the adverse effects of climate change, pollution, and rising sea levels in the future from current trends, what kind of signals would it give before we reach limits? How can this become an urban immune system that calls for action?
