Implementing Advanced Knowledge
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4.2.2 City sensing and parametric strategies for urban planning Andrea Galli
City sensing and parametric strategies for urban planning. Nowadays the urban environment represents a sensitive entity that, in the same way it happens for biological entities, is able to gather information about his single parts, but also about his inhabitants and what happens inside it. In fact, the technology that pervades the spaces we live inside and the objects we use could properly be imagined as the nervous system of the city. The forecast made in 1997 by Mike Batty , architect, urban designer and professor at MIT, that within 2050 everything around us will be some kind of computer, is already close to be realised. To comprehend it is sufficient to think that, for example, in Birmingham all streetlights are equipped with sensors able to collect information about the sky coverage in every moment of the day, with an incredible resolution. The faculty of objects to be a source of digital information is part of the internet of things phenomenon and, thanks to spread of miniaturized sensors and non-invasive data transmission technologies, it represents a reality where, today, we are totally sink into. If the sensors are well disseminated and the data gathered in order to allow connecting them to the precise spatial coordinates they refer to, it is possible to create a real time updated virtual model of the physical environment. In relation to the different sets of data acquired, these can so produce informative scenarios linked to different aspects of the physical space. The huge range of potentials it is possible to perceive is further extended by the spread of portable devices such as smartphones and tablets that every citizen continuously holds and uses, in fact they are heaps of technologies able to constantly collect information: ordinary actions of the everyday life such as making a phone call, updating the Facebook profile, publishing Figure 1 - Demographic distribution in Turin 2
a tweet or paying through a credit card leave a voluntary or involuntary track in the wide urban communication network. The collection of these tracks generates an outright digital layer, overlapped on the real one, repository of the enormous aggregate of the singular experiences intertwining inside our cities. From the possibility of thinking to each citizen as a human sensor, rises the concept of “crowd sensing”. It allows to involve the internet in bottom up processes, contrary of the top down ones that, by definition, distinguishes the structure of a network of sensors where data converges to a single centralized server so to be aggregated and elaborated. The necessity of visualizing in the best way possible this new digital layer of data about the city, has resulted in - data visualization - a discipline widely developed in the last few years, that allows a deeper level of comprehension of the phenomenon of the city and its transformation.
“According to Mike Batty, within 2050 everything around us will be some kind of computer”
All this represents an incredible opportunity in planning the city of tomorrow, but it is not enough. To find the right answers to the questions that “big data” generate about the world we live in we can resort to the potential offered by parametric tools in elaborating with total control, the new resources available, which would be unmanageable and redundant in traditional analysis and planning processes. In order to prepare our cities to become “Smart” it is necessary to adapt the design process that rules the change. In fact, despite many famous examples suggest the opposite, the parametric approach is not based on the shape, but his foundations lie in the relationship between every elementary parts of a complex system where if an element changes, all the other elements will self-organize. This behaviour, called “adaptive”, allows to design systems where once the rules that describe the relationships between every element are set down, if the system changes unexpectedly (emergent behaviour), it will transform itself according to these rules, defined as parametric variables.
Figure 2 - MIT Live Singapore 4
Parametric Urbanism allows us to understand and to control the behaviour of a complex system, such as our cities or parts of them, in order to plan his reaction to the real time change of the data context around it. To describe this context it is necessary to make a selection of data; this inherently represents an important design choice, because it deeply influences the final result. In addition to data typologies, the source of them is in the same way very important: data for example can be open data released by public administrations, freely available to everyone; these data can be easily found on the Internet and embody the social and economic aim of unlocking the potential value of a huge quantity of information, usually under-used. The overlap of vector data and metadata results in a hybrid model that allows to exploit parametric modelling tools in association with a new informative dimension. A thinkable use of a certain model could be the visualization and the interrogation of the database, as with GIS. However it is possible to explore some more interesting direction processing the database in order to generate an unlimited range of potential design proposal on different scales. Taking inspiration from the approach suggested by Anas Alfaris within his PhD thesis Emergence through Conflict: The Multi-Disciplinary Design System (MDDS), developed at MIT under the supervision of W. J. Mitchell in 2009, we can think to structure the all design process using a dynamic and holistic framework divided in five phases according to reversible connections but meanwhile maintaining a robust hierarchic organization. The five phases are decomposition, formulation, modeling, integration, and exploration and can be referred to different design stages: decomposition and formulation belong to the planning stage, modeling and integration belong to the implementation stage, the exploration represent the final verification stage where the previous phases can be validated or rejected.
The decomposition requires dividing the global project vision into elementary units and goals. The formulation contemplates the specific analysis of every single goal so to independently define the processes to realize it, but also the way in which they influence each other. During modeling every goal is developed in a cluster in order to transform into algorithms, thanks to the parametric tool, what was defined during formulation. The integration consists in implementing the relationships between the different clusters, until now described as isolated elements. The exploration is the phase that allows to verify the match between results and what was expected during formulation. In fact, the integration can easily generate unexpected consequences, that will eventually require the process to be reviewed starting from modeling. The described flow chart represents a structured way to manage the design process of complex entities such as our cities. Following it parametric tools can assume the role of an extremely flexible platform to organize into a single data stream large scale data, which come from different sources, describing their relationship through mathematic rules but also counting on the huge 3D modelling chances offered by software. The opportunity of a real time comparison of many alternative scenarios, obtained by changing the mutual influence of the system parameters, is a scientific method for an organic design of our cities considering the phenomenon and the necessities revealed by data and ensuring consistency with the project constrains and goals.
Figure 3 - Big Data Visualisation 6
Figure 2 - Human/Urban Data collected by Smart Planning Lab for representing Palermo’s social and urban metabolism: energy consumes
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