Fran Castillo

Fran Castillo (@francastillo) is an Architect/ETSAS and Interaction Designer/UPF. He is currently research director at Responsive Environments.

parametric design, architecture and art

Image Above : Capacity for (Urban Eden, Human Error). Allison Kudla.

Algorithm as a Model. Closed System VS Open System.

In contrast to the field of architecture and engineering, where the concept of ‘model’ is understood to be a geometric description of objects or (‘Static Models’), the model that we propose is the description of computational algorithms in a generative design process (‘Algorithm as a Model’). These algorithms are instructions, simple rules which evolve multiple states. These new models therefore allow us to simulate the complexity of urban and architectural systems. These dynamic simulations may enable us to understand how systems work or how spontaneous pattern formations occur.

In the ‘Algorithm as a Model’ paradigm, script runs as a process with input and output variables relating to datasets which are processed in real time. These processes can be implemented by using parametric processes to produce an infinite series of possible outcomes.

Generative Systems design is a process in which the material and medium is algorithmic. Algorithms manifest dynamic and emergent behaviour.

Generative Systems propose to shift the focus from static models towards a computational logic, what Bruce Sterling calls Processuality. Processuality is a postmodern change in design perception, inspired by the craft of software. The world is rich with processuality- the growth of plants, boiling liquid, chemical patterns- processuality is all around us.

These Generative Systems allow us to establish relations between patterns, structures, processes, forms and to model evolutionary behaviours. These  techniques enable to simulate real-world phenomena.

The models we propose are articulated around different descriptions of the system concept. The first one, Static Models operate under the definition of a Closed system: “An isolated system having no interaction with an environment [...] a System whose Behaviour is entirely explainable from within, a system without Input.” (Marius Watz).

The second model we propose, Algorithms as a Model is articulated around the description of Open System: “A group of interacting, interrelated, or interdependent elements forming a complex whole.” (Marius Watz).


Image Open Energy. Real-Time Energy Behaviour Visualization. Fran Castillo.

Internet of Cities. City Data Sensing. Real-Time City.

We are currently engaged in exploring new models of dynamic cities.  In parallel to the evolution of the model “Internet of Things”, in which the micro computation is embedded in the design of objects, the model Internet of Cities is emerging: it consists in multiple interconnected layers – energy, mobility, information – as an example of one of its layers, the Internet of Energy. It proposes a new model of distributed generation and energy management based on info-energetic infrastructure. In the model, Internet of Cities, the computation is distributed in urban infrastructure, the deployment of sensing technology allows the monitoring of different urban, environmental, energy parameters. This technology produces a large amount of data (Big Data). The exploration and analysis of these data structures through the design of visualization systems (and interaction) which will allow us to reveal new dynamics of behavior in the city. Around the confluence between the city and data (Data Sensing City) emerges the concept Real-Time City, in which it explicits an evolutionary dimension, auto adaptive, dynamic in the informational systems that constitutes this new model of city, therefore citizens can change their patterns of behavior in relation to these information systems, creating a dynamic reconfiguration of the city.

How will it be, the evolution of cities in the Internet of Cities? Can Real-time City generate new forms of governance, participation, analysis and information management?