Large-Scale Urban Prototyping for Responsive Cities: A Conceptual Framework

Despite ubiquitous urbanization and worldwide standardization, there is a lack of better differentiation between cities toward more customized environments. Although current advancements in computational design and digital fabrication technologies have been successfully applied in various architectural scales, they have rarely, if ever, been implemented in a larger urban context that can lead to broader benefit and responses for citizens. This research aims to describe the potential of digital fabrication methods for large-scale urban applications that can subsequently lead to more diverse and unique urban environments. This paper summarizes state-of-the-art principles for large-scale building construction that have been implemented in the past, along with current research and practice, and outlines a conceptual framework for possible future directions for large quantities of automatic and bespoke construction deliveries for future customized urban scenarios. This article also outlines the effects of end-users' participation on urban developments using online users' interface to inform building processes. To address aspects of end-users' engagement in customization of cities, the article elaborates the question of responsiveness, where the citizen actively interacts with the environment and building technology and vice versa in order to customize the urban space. This is theoretically and conceptually explained and illustrated in a case study related to the formerly industrial harbor area of Tanjong Pagar in the city of Singapore, which is a test-bed for new urban developments on 325 ha of waterfront land in the downtown port area within the context of a tropical city

On-site Participation for Proto-architectural Assemblies Encompassing Technology and Human Improvisation: “Fish Trap” and “Orchid” Architectural Interventions

This research investigates the notion of builders’ on-site engagement to physically build architectural interventions based on their demands, spatial requirements and collaborative improvisation, enhanced with the principles of uniqueness and bespoke solutions previously explored in computational models. The paper compares and discusses two physical installations as proto-architectural assemblies testing two different design and building approaches: the top-down predefined designers’ scenario contrary to bottom-up unpredictable improvisation. It encompasses a building strategy based on the discrete pre-cut components assembled by builders themselves in situ. The paper evaluates both strategies in a qualitative observation and comparison defining advantages and limitations of top-down design strategy in comparison with decentralised bottom-up building system built by the builders themselves. As such, it outlines the position of a designer within the bottom-up building processes on-site. The paper argues that improvisation and builders’ direct engagement on-site leads to solutions that better reflect human needs and lower-tech building principles incorporated can deliver unpredictable, but convenient spatial scenarios

Customised Floating Neighbourhoods: Design Interfaces for Non-experts and Designers to explore Emergent Floating Formations

Urban water spaces, lakes and rivers have played a key role in socio-economic and spatial development of cities throughout centuries. There is an increasing trend in creating floating neighbourhoods and spaces on water worldwide. Design of floating urban spaces is complex; it requires incorporation of advanced computational tools to ensure correct interpretation of environmental conditions to make proper design decisions. In this study, we focus on an investigation of possibilities of floating neighbourhoods to adapt according to rapid changes of environments and demands of their end-users to address deeper engaging of non-experts in the decision and design processes. In so doing, we proposed modular assemblies as a floating neighbourhood, designed and tested computationally using advanced modelling techniques to address potentials of floating systems to grow and create formations in waterfront cities. In this paper we tested 2 possible spatial developments of floating configurations in order to understand non-experts’ preferences captured from an in-house developed computational model in comparison with designer’s digital assembly strategies to deliver various emergent complex scenarios of urban development

Urban Autopoiesis: Towards Adaptive Future Cities

A city, defined as a unity of inhabitants with their environment and showing self-creating and self-maintaining properties, can be considered as an autopoietic system if we take into account its bottom-up processes with unpredictable behaviour of its components. Such a property can lead to self-creation of urban patterns. These processes are studied in well-known vernacular architectures and informal settlements around the world and they are able to adapt according to various conditions and forces. The main research objective is to establish a computational design-modelling framework for modelling autopoietic intricate characteristics of a city based on an adaptability, self-maintenance and self generation of urban patterns with adequate visual representation. The paper introduces a modelling methodology that allows to combine planning tasks with inhabitants` interaction and data sources by using an interchange framework to model more complex urban dynamics. The research yields preliminary results tested in a simulation model of a redevelopment of Tanjong Pagar Waterfront, the container terminal in the city of Singapore being transformed into a new future centre as a conducted case study

CAD integrated workflow with urban simulation-design loop process

The urban space nowadays is considered as an aggregate of large amount of complex characteristics. Information collected by means of urban big data approaches play a crucial role in how to understand, interpret and model urban environments. Simulation models are the best solution for architects, urban planners and designers to integrate various information about urban complexity into the design process. The connection between several simulation approaches within one user interface is still a big challenge to make the design process faster, more accurate and visually convenient. The interface would be involved in the modelling process, pre-processing, simulation, post-processing and visualisation. A CAD integrated user interface is proposed where all these particular components are embedded into one system. The whole process would be based on a workflow loop whereby each component will be depending on the previous cycle. As a case-study of such a principle we establish an extendable modelling and simulation platform connected to a user through the game-engine Unity3D in order to achieve a robust interactive environment. The model platform operates with real urban conditions of an existing part of the city of Singapore and simulates the distribution of traffic’s heat within the investigated environment. Based on the simulation results the user can configure more proper spatial scenarios within the urban plan in different variations. The proposed system would help architects and urban planners to enhance their decision repertoire during the design phase and allows them taking into account more complex information about the urban entirety. The result of the research is therefore a computational decision-making tool with enhanced visual output

Fish Trap - A floating Proto-assembly for Responsive Cities: Towards Citizen-Driven Customised Water Urban Spaces

Urban water spaces, lakes and rivers have an impact on the image of the city and have played a key role in the socioeconomic development of cities throughout the centuries. This positive trend makes the redevelopment of waterfronts an ideal test-bed for new concepts of citizen engagement and adaptive and responsive architectural designs. Unfortunately, waterfronts often change and change is activated from bottom-up, but even today, we can not actively engage the users in the design process. Hence, in this project, we will build a floating proto-architectural system, consisting of a set of simple pre-defined modules which can be assembled, re-assembled and assembled again in different configurations by the end users (citizens) on-site, leading to a diverse number of more complex architectural and spatial variants. Water, as a key environmental and architectural feature of a given space, will serve as a medium for adaptability, flexibility and interaction with the city. Our proto-assembly will behave like an ancient FISH TRAP; but this time in London, in waters of Thames; our novel fish trap will harness latest material, technological and computational achievements and digital fabrication methods together with robust architectural design practices. The users will transform the old design idea of simple fish trap to a unique proto-architecture

Big-Data Informed Citizen Participatory Urban Identity Design

The identity of an urban environment is important because it contributes to self-identity, a sense of community, and a sense of place. However, under present-day conditions, the identities of expanding cities are rapidly deteriorating and vanishing, especially in the case of Asian cities. Therefore, cities need to build their urban identity, which includes the past and points to the future. At the same time, cities need to add new features to improve their livability, sustainability, and resilience. In this paper, using data mining technologies for various types of geo-referenced big data and combine them with the space syntax analysis for observing and learning about the socioeconomic behavior and the quality of space. The observed and learned features are identified as the urban identity. The numeric features obtained from data mining are transformed into catalogued levels for designers to understand, which will allow them to propose proper designs that will complement or improve the local traditional features. A workshop in Taiwan, which focuses on a traditional area, demonstrates the result of the proposed methodology and how to transform a traditional area into a livable area. At the same time, we introduce a website platform, Quick Urban Analysis Kit (qua-kit), as a tool for citizens to participate in designs. After the workshop, citizens can view, comment, and vote on different design proposals to provide city authorities and stakeholders with their ideas in a more convenient and responsive way. Therefore, the citizens may deliver their opinions, knowledge, and suggestions for improvements to the investigated neighborhood from their own design perspective

Empowering Urban Design Prototyping: A Case Study in Cape Town with Interactive Computational Synthesis Methods

Although Cape Town city in South Africa is generally regarded as the most stable and prosperous city in the region, there are still approximately 7.5 million people living in informal settlements and about 2.5 million housing units are needed. This motivates the so-called Empower Shack project, aiming to develop upgrading strategies for these informal settlements. To facilitate the fulfilment of this project, urban design prototyping tools are researched and developed with the capabilities for fast urban design synthesis. In this paper we present a computational method for fast interactive synthesis of urban planning prototypes. For the generation of mock-up urban layouts, one hierarchical slicing structure, namely, the slicing tree is introduced to abstractly represent the parcels, as an extension of the existing generative method for street network. It has been proved that our methods can interactively assist the urban planning process in practice. However, the slicing tree data structure has several limitations that hinder the further improvement of the generated urban layouts. In the future, the development of a new data structure is required to fulfil urban synthesis for urban layout generation with Evolutionary Multi-objective Optimisation methods and evaluation strategies should be developed to verify the generated results

Computational urban design prototyping: Interactive planning synthesis methods—a case study in Cape Town

This article is motivated by the fact that in Cape Town, South Africa, approximately 7.5 million people live in informal settlements and focuses on potential upgrading strategies for such sites. To this end, we developed a computational method for rapid urban design prototyping. The corresponding planning tool generates urban layouts including street network, blocks, parcels and buildings based on an urban designer’s specific requirements. It can be used to scale and replicate a developed urban planning concept to fit different sites. To facilitate the layout generation process computationally, we developed a new data structure to represent street networks, land parcellation, and the relationship between the two. We also introduced a nested parcellation strategy to reduce the number of irregular shapes generated due to algorithmic limitations. Network analysis methods are applied to control the distribution of buildings in the communities so that preferred neighbourhood relationships can be considered in the design process. Finally, we demonstrate how to compare designs based on various urban analysis measures and discuss the limitations that arise when we apply our method in practice, especially when dealing with more complex urban design scenarios

Machine learning approaches to understand the influence of urban environments on human’s physiological response

This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequency unification, signal pairing, signal filtering, signal quantification, and data labeling. Furthermore, this paper contributes to human-environment interaction research, where a field study to understand the influence of environmental features such as varying sound level, illuminance, field-of-view, or environmental conditions on humans’ perception was proposed. In the study, participants of various demographic backgrounds walked through an urban environment in Zürich, Switzerland while wearing physiological and environmental sensors. Apart from signal processing, four machine learning techniques, classification, fuzzy rule-based inference, feature selection, and clustering, were applied to discover relevant patterns and relationship between the participants’ physiological responses and environmental conditions. The predictive models with high accuracies indicate that the change in the field-of-view corresponds to increased participant arousal. Among all features, the participants’ physiological responses were primarily affected by the change in environmental conditions and field-of-view