Thesis topic proposal
Bálint Kádár
Data Driven urban Design: Planning oriented Smart City models based on the space usage of locals and visitors


Institute: Budapest University of Technology and Economics
Pál Csonka Doctoral School of Architecture

Thesis supervisor: Bálint Kádár
Location of studies (in Hungarian): BUTE
Abbreviation of location of studies: BUTE

Description of the research topic:

In the age of Big Data urban planning and design is still rarely capable to apply much of the new methods of data analysis, while the speed of social and technological changes is higher than ever, therefore it would be necessary to understand urban processes based on up-to-date data, and to be able to use these for design. Cities use only little of the data coming from the ICT technologies of urban infrastructures or from social media used by locals and travellers. Transport optimization (FUTÁR, Waze…) or crime prevention (closed circuit cameras…) systems allow immediate intervention based on data, but other systems with slower reaction times (due to the need of extensive planning and implementation times) would also benefit from more knowledge on the behaviour and needs of city users. Only with up-to-date data and comprehensive smart city models can the design of new urban areas or the redevelopment of old neighbourhoods be successful today.

Analysing data from social media (Instagram, Flickr, tripadvisor…), or the ICT systems of urban infrastructures (Bubi, Futár, AirBnB, ingatlan.com…) it is possible to map the behaviour of user groups in urban space. It is possible to understand contemporary patterns of urban space usage from the visualization and analysis of such data (tourism, leisure-time or commuting patterns, bicycle usage…). The goal of such analysis should be the creation of a comprehensive urban modelling capable to present and predict with better accuracy the functioning of some of the cities systems, allowing the data drive design of these.

In Urban planning there are already developed methods to model and analyse spatial systems. The most used method for analysis and design is Space Syntax, based on morphological analysis, but capable to predict social processes in space. Even scholars using this methodology struggle with the integration of user generated data to extend its usability in planning. Therefore, the development of new methods to model urban systems using similar network-based approach but based on real behaviour data should have a great impact for both science and planning. To arrive to such models the following steps will have to be followed:
- identification of the proper database for the processes to be modelled
- data analysis following an exact methodology allowing the quantification of results, and their verification
- the creation of a spatial and/or network model based on the data analytics
- proof of the model’s usability for planning
- proper software usage for the acquiring of data (API manager), handling of the database (GIS, datasheets), and analysing the model (Space Syntax, graph analytic software)
The goal of the research is to be able to arrive to Data Driven Design methodologies using consistent models for the given urban systems.

Further description: http://cspdi.bme.hu/files/doktori/meghird_temak/Temahird_Kadar%20Balint_DDuD_2020.pdf

Deadline for application: 2022-03-31

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