Designing with Data:
Collective Intelligence in Urban Design
by
Helena Hang Rong
B.Arch. Cornell University, 2017
Submitted to the Department of Architecture in partial fulfillment of the requirements for the
degree of Master of Science in Architecture Studies at the
Massachusetts Institute of Technology
JUNE 2019
© 2019 Helena Hang Rong. All rights reserved.
The author hereby grants to MIT permission to reproduce and to distribute publicly paper and
electronic copies of this thesis document in whole or in part in any medium now known or
hereafter created.
Signature of Author: ____________________________________________________________
Department of Architecture
May 21, 2019
Certified by: ___________________________________________________________________
Miho Mazereeuw
Associate Professor of Architecture and Urbanism
Certified by: ___________________________________________________________________
Sarah Williams
COMMITTEE
Thesis Co-Supervisor: Prof. Miho Mazereeuw
Associate Professor of Architecture and Urbanism
Thesis Co-Supervisor: Prof. Sarah Williams
Associate Professor of Technology and Urban Planning
Thesis Reader: Prof. Jennifer S. Light, PhD
Department Head, Program in Science, Technology, and Society; Bern Dibner Professor of the
History of Science and Technology; Professor of Urban Studies and Planning
Thesis Reader: Prof. Eric Gordon, PhD
Professor and Director of the Emerson College Engagement Lab
Designing with Data:
Collective Intelligence in Urban Design
by
Helena Hang Rong
Submitted to the Department of Architecture on May 22, 2019 in Partial Fulfillment of the
Requirements for the Degree of Master of Science in Architecture Studies.
ABSTRACT
Over the last decade, advancements in data collection, computing and visualization methods have given rise to a new form of urbanism: networked urbanism. Our current output of data is roughly 2.5 quintillion bytes a day. Ninety percent of the world’s data has been created in the last two years alone. As cities compete for “smart city” status, myriad sensors are installed in the built environment, capturing a “real-time” city supposedly responsive to both infrastructural and citizen needs, thereby creating a more desirable environment for people to live. If this is the case, why has Songdo International Business District become a “ghost-town” as some reports claim, attracting only less than a quarter of its anticipated population? Although the smart city model has been hailed by technocratic enthusiasts as a solution to the sustainable city challenge for almost two decades, it has increasingly been critiqued for being overly technocratic and top-down in orientation, decreeing forms of algorithmic governance which control and discipline citizens, and omitting qualitative factors such as cultural vibrancy and community bonding. And in the process, both designers and citizens become increasingly marginalized from the discussion. I intend to address the shortcomings of current approaches to Smart Cities in the context of human-centric urban design and develop a new design methodology which emphasizes on the “smart citizen” to effectively engage the collective throughout a collaborative urban design process. This thesis surveys a number of significant recent projects and studies their goals, proposed frameworks and interventions, ingredients used in their IoT solutions as well as potential concerns, and uses the findings to create a citizen engagement tool and design framework to be tested on a site in Ang Sila, Thailand.
DESIGNING WITH DATA
Collective Intelligence in Urban Design
ACKNOWLEDGEMENTS
To the following individuals who have given me immense support in the pursuit of this thesis, my deepest gratitude goes to you:
My dear co-advisors Miho and Sarah, your valuable insights, knowledge and support have guided me along the way throughout this semester; my readers Jennifer and Eric, for you expertise and knowledge which have helped refine the frameworks of the thesis; Chat, for your hospitality in Thailand, for sharing with me your knowledge and research about Ang Sila, for taking me on crucial site visits which constitutes a huge part of this research; Bom, Puping and Supang, for your hospitality and warm welcomes in Thailand; to my dearest friends at MIT: Kailin, Juncheng (Tony), Yue (Will), Alina, Kyle, Sea Hoon, Jennie, Darle and Moon, for daily inspiration and for starring different characters during my final presentation; JWQ, for your remote render support; to mom and dad, for your unconditional love and encouragement. This thesis could not have been done without you.
TABLE OF CONTENTS Chapter 1 Introduction 1.1 A Global Phenomenon 1.2 Research Questions 1.3 Methodology 1.4 Intended Contribution
Chapter 2 Background and Literature Review
2.1 Urban Informatics, Big Data, Internet-of-Things and Smart Cities 2.2 From “Smart City” to “Smart Citizen”
2.3 Citizen Science, Citizen Participation and Citizen Design Science 2.4 Spatial Agency
2.5 Stacked Theory and Networked Urbanism 2.6 Actor Network Theory
Chapter 3: Case Studies: Projects and Tools
3.1 Neighborhood Scale: Sidewalk Toronto, Quayside, Ontario 3.2 City Scale: Songdo International Business Districts, South Korea 3.3 National Scale: Estonia
3.4 An Inventory of Digital Participatory Methods, Research & Tools Chapter 4: Collective and Individual Data
Chapter 5: A Framework Proposal
Chapter 6: Design Speculation: Ang Sila, Chonburi, Thailand Chapter 7: Design of Tool
Chapter 8: Deployment on Site
Chapter 9: Reflection, Discussion and Future Launch Chapter 10: Bibliography 08 09 09 10 11 14 14 19 20 21 24 26 30 32 33 39 41 46 64 72 136 138
Chapter 1: Introduction 1.1 A Global Phenomenon
Over the last two decades, advancements in data collection and computing is giving rise to a new form of urbanism: networked urbanism, which is data-driven solutions informed by connected infrastructure and things. With this, there is an ongoing global trend: city-making and urban creation are no longer led by architects and urban designers, but rather technology conglomerates with vast means to capture and analyze data, who promise to address challenges of urban governance with data collection and analysis tools, in order to enhance management and efficiency. The shift towards networked urbanism and the rise of technology conglomerates represent a fundamentally different attitude towards urban creation, a trend suggesting a diminishing role of architects and urban designers. The vague conceptual framework of the “smart city” is an example of encompassing strategies of optimizing various indices of performance. As cities compete for “smart city” status, myriad sensors are installed in the built environment. What’s common about these sensors are that they passively collect information about the city without consent or direct involvement of citizens. But as some extreme cases illustrate, such as Songdo International Business District, smart city will not succeed if innovation only focuses on advanced technologies, rather than on community development and engagement.
Another City is Possible: Net-worked Urbanism from Above and Below., Adam Greenfield.
1.2 Research Questions
This thesis attempts to address several questions: 1. How is digital participation changing the role citizens/ end-users play in urban planning/design and decision-making processes?
2. What digital tools can be developed to facilitate the interaction between different players in shaping the city?
3. How can designers use this data to negotiate various interests of different social groups through designing spatial adjacencies, shared spaces, and hybrid programming?
1.3 Methodology
To contextualize the problem, I am testing the process and tool on a site in Thailand called Ang Sila, 1.5 hours away by car and 91 km southeast of Bangkok. Using a tool and framework I have developed, which consists of both physical (kiosk stations) and digital components (Chatbot and web interface), I run through a hypothetical development process on the site which demonstrates various use cases to see how the process and tool can be deployed and become useful throughout different phases. After a thorough site visit to Thailand in late March and forming an understanding of existing spatial conflicts and demographic diversity, I have created a cast of characters with unique profiles and priorities. The tool collects input from the users during different stages, which lead to meaningful design questions. The user experiences the feedback process mostly through the mobile end in social media Line Chat, where they receive questions and respond to give their input in the form of text, images/videos, and votes. The open-source web platform geospatially
perspectives lead to increasingly optimized design solutions.
1.4 Intended contribution
While digital culture of the Internet in general has embraced collaborative methodologies inherent in technical logic of digital tools such as “open-sourced” software and involving participation of citizens using ICT, the discipline of architectural and urban design has fallen behind on adopting participatory and interactive aggregation, leaving a gap for exploration of how collective intelligence through citizen engagement could be enabled, and how this information could help designers improve their designs in an iterative process. After a deep dive of research into existing digital
participatory tools and methods and evaluating pros and cons of each, I have developed a design process which facilitates continuous conversation between end-users with other official stakeholders, and a system and tool which could interface between designers and end-users throughout different phases of a project.
My work will contribute to the efforts in the design field which have aimed to develop systems that facilitate digital participatory processes between designers and end-users. While most of these examples exist in black box environments, I propose to create an open-source interface mediated by the designer to allow design to happen iteratively between different agencies based on constant user feedback.
Chapter 2: Background and Literature Review
This chapter gives an overview of multiple disciplines that have influenced the conception and development of networked urbanism (Blokland-Potters et al.,
2008), empowered by conglomerations of data and computation. The excessively technocratic approach to smart cities has led to recent rethinking of the discourse from “smart city” to “smart citizenship.”
2.1 Urban Informatics, Big Data, Internet-of-Things and Smart Cities
Existing since 1980’s, Urban Informatics is understood as “the study, design, and practice of urban experiences across different urban contexts that are created by new opportunities of real-time, ubiquitous technology and the augmentation that mediates the physical and digital layers of people, networks and urban infrastructures” (Foth, Choi, Satchell, 2011, page 4). A decade before, Manuel Castells has already outlined the ontological difference between ‘a space of places’ and ‘a space of flows’ in The Rise of the Network Society (Castells, 1996) shaped our understanding of cities as containing both experiences and activities that literally take place, and the rapid movement of capital, communication, and people going from one place to another. In a way, Castells describes a binary which sees the physicality of “place” and the intangible layer of “flow” as distinctly separable urban layers. However, this distinction is no longer sufficient to help us understand in present day where these two worlds come together as entwined relationships between people, place and technology in the digital age enabled by a new palette of innovative tools.
In a Colloquium held in 2006 at the University of Durham, Visual Artist Amanda Williams, Professor of Media, Culture and Communication Erica Robles and Computer Scientist Paul Dourish then defined urban
on technology and computation, urban informatics underpins the social and human implications of technology and its relationship to cities, (Foth, 2009) engaging with literatures from diverse theoretical resources in cultural studies, design theories and geography to understand sociology from the outset. Major contributions over the years include writings of Rob Kitchin and Martin Dodge, Scott Lash, Nigel Thrift, Stephen Graham and Mike Crang, Anthony Townsend, Roger Burrows and David Beer, Bill Mitchell, Bruce Sterling and Katherine Hayles. These scholars have attempted to define and clarify the new relationship found between computational agents of information and human behaviors in urban space.
In his recent essay, “Capitalism and Metaphysics,” cultural sociologist Scott Lash contends that information is no longer just epistemological, but is rather becoming increasingly ontological— “[w]hat was a medium…has become a thing, a product”– information has become an active agent in constructing the world (Lash, 2007). Lash’s understanding of information corresponds with a position held by Thrift and French, where they maintain that the “technical substrate of … societies…has changed decisively as software has come to intervene in all aspects of everyday life… [,which is] a means of providing a new and complex form of automated spatiality, complex ethologies of software and other entities which, too often in the past, have been studied as if human agency is clearly the directive force … which has important consequences for what we regard as the world’s phenomenality” (Thift & French, 2002, 209). Adding to this perspective, Dodge and Kitchin examine software from a spatial point of view, stressing Code’s ability to produce space and shape the material world (Dodge & Kitchin, 2004). For geographers Crang and Graham, the study of urban informatics accounts for the assemblages created by emerging technologies used to govern human action across time and space. They classify three distinct but related approaches to digital spatialization as augmented space, enacted space, and transducted space, to describe augmented virtual space, software as an extension of human agency and software sorted geographies (Crang and Graham, 2008, 792-4). The last category is especially interesting because it addresses
the potentialities of technological agency, (Dodge & Kitchin, 2005) in which Hayles explains through a notion of a ‘cognisphere’ where human agency is just a part of a larger assemblage of interconnected agencies (Hayles, 2006, 7-8).
Planning and Design:
Alongside theoretical developments in the form of writing, much applied experimentations with data science and urban informatics take place in institutional research lab settings, where projects funded by
governmental bodies or practical industry experiment with new tools to promote the application of urban science to improve cities. MIT’s SENSEable City Lab led by Carlo Ratti, has for more than ten years championed tools for urban informatics in producing applications and graphic representations of “real-time cities,” with goals of revealing otherwise invisible complex trends and behaviors of the urban environment, in what Urban Digital Designer Sarah Barns terms “App-tivism” enabled by the use of mobile phones (Barns, 2017). The bulk of SCL’s research endeavor has been dedicated to generating data visualization through web platforms or mobile apps to capture highly-informationalised urban spaces where users are encouraged to contribute data to illuminate information patterns as the “soft infrastructure” layer of the city. Project Real-time Rome is such an example where mobile phones and GPS devices are used to collect the movement patterns of people and transportation systems and their spatial and social use of streets and neighborhoods, which are then communicated back to the user via an interactive display screen developed by the lab. SCL’s work, along with that of many other key players in the field, including the Future Cities Laboratory from ETH, Queensland University of Technology’s Urban Informatics Research Lab, belongs to the claim that new digital platforms such as smartphones can be used to transform the way our cities are understood from a “traditional” urban planning perspective, championing ubiquitous technologies and sensors as “citizen-centric”
2.2 From “Smart City” to “Smart Citizen”
Spearheaded by technology companies without expertise in urban design and planning, Smart City planning tends towards technological solutionism (Morozov, 2013). Although the smart city model has been hailed by technocratic enthusiasts as a solution to the sustainable city challenge for almost two decades, it has increasingly been critiqued for being overly technocratic and top-down in orientation, decreeing forms of algorithmic governance which control and discipline citizens.
What is currently missing in the discussion of urban informatics is a clear definition of the relationship between people and the data they produce as well as the relationship between their agencies. This gap raises concerns regarding surveillance, digital divide, centralized governance and ownership of data, which all contribute to an overall growingly negative sentiment towards the “smart city.” However, a very recent strategy presented by British architect Jason Pomeroy in his eight-part series on smart cities, Smart Cities 2.0, begins to suggest human-centered technologies and possibilities of engaging citizens in the design and planning process using technology (Pomeroy, 2017). As the field has evolved over the past decade, initial optimism of urban informatics has waned and partly been replaced with skepticism. The same proponents of its theories from the early days now caution against the co-optation of platform technologies by corporate powers, particularly in relation to critiques of the smart city (Barnes, 2017, 10). In his manifesto Smart Cities: Big Data, Civic Hackers and the Quest for a New Utopia, American technology consultant Anthony Townsend warns his readers against technology control systems disguised as sustainable urbanism that obliterate innovative capabilities of the digital platforms –
openness, interoperability and innovation, and calls for a renewed focus on “smart citizen” (Townsend, 2013).
2.3 Citizen Science, Citizen Participation and Citizen Design Science
2.31 Citizen Science
Here, I would like to address citizen science as an “The Smart Enough City” by Ben Green
“By recognizing the complexity of urban life rather than merely seeing the city as something to optimize, these Smart Enough Cities successfully incorporate technology into a holistic vision of justice and equity.”
use of ICT solutions in involving participation of citizens in research led by professionals. Citizen science refers to scholars in Education Richard Adler and Judy Goggin’s definition of “the ways in which citizens participate in the life of a community in order to improve conditions for others or to help shape the community’s future” (Adler & Goggin, 2005). Citizen science is a contemporary reinvention of ancient research practices when non-professionals contribute to scientific
research led by academics. The term was originally defined in the mid-1990’s independently by ornithologist Rick Bonney from the United States and sociologist Alan Irwin from the United Kingdom. Irwin’s definition of Citizen Science is: “developing concepts of scientific citizenship which foregrounds the necessity of opening up science and science policy processes to the public (Irwin, 1995). These involve technology-enabled citizens as trustworthy agents actively contributing to scientific experiments (Irwin, 1995). Referring to “a volunteer who collects and/or processes data as part of a scientific enquiry,” (Silvertown, 2009, 467-471) a citizen scientist could contribute to large-scale projects that require a vast amount of data to be collected across an array of locations and habitats. In the 21st century, the practice takes advantage of the usability of software and mobile computing, to allow non-professionals to gather and share data to work towards a common scientific research goal. To date, citizen science projects mainly reside in the environmental science domain. Notable successful citizen science projects include Christmas Bird Count which has existed for hundreds of years, and GalaxyZoo, which asks participants to classify astronomical photographs based on their appearance (Crowston & Prestopnik ,2013).
There are three levels of Citizen Science according to Bonney et al. that refer to various levels of engagement (Bonney et al., 2009). Projects such as the Bird Count utilizing crowdsourced data collection require the least active input from the citizen scientist; collaborative projects that consist of both data collection and data analyses demand a higher level of critical thinking and
in tandem with urban computing methodologies foster a participatory urbanism to enable citizen action by allowing open measuring, sharing, and remixing of elements of urban living marked by, requiring, or involving participation (Paulos & Honicky, 2009).
2.32 Citizen Participation
In the field of planning, Sherry Arnstein’s influential paper from 1969 entitled “A ladder of citizen
participation” provides a heuristic device for structuring her argument as eight rungs “corresponding citizens’ power in determining the end product,” (Arnestein, 1969). Coming from a practical background in housing and policy, Arnstein’s understanding of citizen
participation does not derive from theory but rather reflects her perspective into federal programs of urban renewal and anti-poverty intervention, which heavily links quality and depth of citizen participation in planning to the direct access to power (Kitchin, 3).
Arnestein’s eight rungs of citizen participation are grouped into three categories. On the bottom, “non-participation” breaks down into “therapy” and “manipulation,” and refers to top-down centralized governance through education and direction of people. In the mid-tier, “tokenism” consists of “placation,” “consultation,” and informing,” which is partial engagement where people have certain levels of autonomy and “voice,” from providing feedback to suggesting interventions, though they rarely are able to change directly the status quo of already
implemented decisions and plans. The final three rungs – “partnership,” “delegated power” and “citizen control” – construct “citizen power.” “Partnership” demands co-creation and collaboration with dominant power-holders; “delegate power” enable citizens to become full actors and have a dominant decision-making role; and in “citizen control,” “have-not citizens obtain full managerial power” (Arnstein 1969: 217).
A recent publication by Paulo Cardullo and Rob Kitchin entitled “Being a ‘citizen’ in the smart city: Up and down the scaffold of smart citizen participation” restructures Arnstein’s ladder to include consumption and choice to reflect the contemporary culture of consumption and commodification of resources.
2.33 Citizen Design Science
A new branch of research conducted at ETH Zurich Future Cities Laboratory and Singapore-ETH Centre led by Post-Doctoral Researcher Johannes Müller expands from the field of citizen science to a novel approach termed “Citizen Design Science.” This model arises from three pillars – Citizen Science, Citizen Design, and Design Science. Citizen Science refers to the participatory aspects of data collection; Citizen Design refers to active design by citizens, and Design Science is employed as a method of translation of citizens’ design proposals into the design of urban designers (Muller et al., 2018). The research sees Kevin Lynch’s strategy of mental mapping as one of the first Citizen Design Science methods.
The Citizen Design Science approach combines crowdsourcing opinions and thoughts by citizens through information and communication technology (ICT) with active design tools the team has developed called the Quick Urban Analysis Kit (qua-kit). This is an early-stage web-based application where users can directly manipulate 3D moveable objects and modify geometric layouts, although only minimally (Muller et al., 2018). However, the researchers have not yet resolved the challenges of evaluating the usefulness of these proposals featuring highly reductive 3D designs or how these designs could become useful feedback for professional designers. Moreover, there is another concern regarding accessibility and familiarity with digital tools – younger people who are more tech- savvy may become the dominant demographics participating in the exercise, thus leaving out those who are less digitally literate. There is pending discussion on how ideas of online design tools can be combined with conventional participation methods commonly used by elderly and non-technophiles (Mueller et al., 2018). Citizen Design Science model proposed by ETH
Zurich Future Cities Labratory and Singa-pore-ETH Centre led by Johannes Muller
2.4 Spatial Agency
Henri Lefebvre’s frequently cited quote “right to the city is a renewed right to urban life” is as relevant now as it has been when he first proposed the idea back in 1968. In the field of architecture and urbanism, a conceptual framework of “agency” has undergone reevaluation to challenge mainstream design metrics in the last ten years. Published in 2011, Spatial Agency: Other Ways of Doing Architecture co-authored by Nishat Awan, Tatjana Schneider, and Jeremy Till claims that spatial agency re-appropriates “traditional” architectural skills to empower others (non-architects) to “engage in their spatial environments in ways previously unknown or unavailable to them, opening up new freedom and potentials as a result of reconfigured social space” and inverting the conventional subject-object (designer-user) relationship in spatial construction (Awan,
Schneider & Till, 2011, 32). In many ways, this approach equalizes and redistributes the notion of agency of the agents and patients from prior professional beliefs and broadens a pragmatic understanding of design as a dynamic and conscious practice. However, what is entirely absent from this scholarship is the role of data and its agency, and the meaning of spatial agency in the age of information.
This is precisely a point highlighted by architectural historian and critic Mario Carpo in his essay“Digital Indeterminism: The New Digital Commons and the Dissolution of Architectural Authorship” from Architecture in Formation: On the Nature of Information in Digital Architecture (2013),which approaches the issue of spatial agency and citizen engagement from a technological perspective (Carpo, 2013). The essay is a critical commentary that underlines the lack of shared agency and the untapped resource of crowd wisdom in current architectural design practice through the lens of technology. Carpo’s argument assesses the digital pattern of devolution of agency from the angle of social bonds and participation. Carpo contends that while digital culture of the Web 2.0 in general has embraced collaborative methodologies inherent in technical logic of digital tools such as “open-sourced” software,
(Carpo, 2013).
The Internet empowers wisdom of crowds not through mere data collection and statistical mean-finding, but through “open-ended mode of ‘aggregatory’ versioning, where the collective knowledge of a community is garnered by inviting all agents to edit one another – in theory, ad libitum atque ad infinitum [and] in practice, under the stewardship of some form of curation” (Carpo, 2013, 48). This aggregation of collective knowledge summates to what Carpo refers to as Adam Smith’s “invisible hand” or “style of many hands,” which transfers individual egoism into a collective wisdom (Carpo, 2013). However, Carpo argues that such culture of communal making pervades in developments of open-sourced software largely in other disciplines, rather than extending to open-sourced design in our own discipline, leaving a gap for exploration of how collective intelligence through citizen engagement could be enabled by data. The key question is not what an Internet city would look like, but a user-generated city.
2.5 Stacked Theory and Networked Urbanism
Benjamin Bratton’s theoretical perspective called The Stack describes a “schema of machines” to illustrate the apparatuses of digital market economy. Contrary to Kitchin and Dodge’s definition of “code/space” mentioned in the beginning of this chapter, The Stack distinguishes from code/space in that it allows for conceptualizing networked urbanism more broadly beyond examination of mere overlay of invisible bits and physical atoms connected through Wi-Fi and IoT. Rather, The Stack describes a comprehensive global computation system which facilitates not only non-human networks of energy generation, data storage, information and communication technologies, but governs users who are “both over-outlined by self-quantification, and … expanded by the introduction of environmental sensors, algorithms, and robots” (Bratton, 2015).
Under current top-down governmental and economic ambitions, cities strive to become a multilayer
networked stack which encompasses all infrastructural and urban elements of the city – from streets to traffic
manner which responds in real-time the needs of infrastructural demands according to fluctuations of urban data. In this way, The Stack perceives the world as information and data points in its attempt to decipher it. Although humans are included in the mix of information, the algorithm does not necessarily prioritize the will of the citizens in its attempt to output the most optimized solution for the city. This thesis proposes an alternative perspective to this model.
2.6 Actor Network Theory
Actor Network Theory is introduced in this section to provide a frame of reference to understand the roles human and non-human subjects play in post-digital urban processes, which further expands the conceptualization of a Smart City and networked urbanism.
Etymologically, the word “agency” is derived from the Medieval Latin word agentia, which means “effective, powerful.” It is also a present participle of agere, which is defined as “to set in motion, drive forward; to do, perform” (Etymonline.com). The field of linguistics identifies a scene of action as consisting of three components: the agent as the subject, the patient as the object, and the “instrument” as the medium used to perform the action which mediates between the actor (agent) and the acted upon (patient) (The Chicago School of Media Theory). In design, such clear role designation may correspond to the conventional binary understanding of roles of designer as agent, citizen as patient, and technology as instrument. However, Actor Network Theory suggests a much more intertwined relationship between different actors and a renewed understanding of their agencies.
Developed by science and technology studies (IST) scholars Bruno Latour, Michel Callon, John Law and others in the 1980’s, ANT contributes through a
“actants” affect the network. This framework is especially relevant because it subjectifies objects to address the relationship of human-beings-non-humans in the context of progressive automation and advanced scientific instruments. Bruno Latour stresses that rather than treating the social as a distinct thing, it is nothing more or less than the typologies of connectivity between a multitude of agencies, from the human to things (Latour, 2005).
ANT’s insistence on the capacity of nonhumans to assume agency has received vigorous criticisms. A particularly relevant critique comes from Social Sciences scholar Langdon Winner, who maintains that such analytic equality between human and nonhuman actors neglects intrinsic properties of intentionality that fundamentally distinguishes the two (Winner, 1993). However, a more recent counter debate from Information Management scholar Jeremy Rose and historian of science and technology Matthew Jones, with which I align my perspective, contends that the nonhuman actors deserve equal interrogation with regards to assessing networks that contain technological elements, while acknowledging the distinction in character and intention between humans and “things” (Rose & Jones, 2005). Rose and Jones formulate their argument in a ‘double dance of agency’ model, which considers machines as achieving equality in the network measured in terms of the “power to act” not through processing equivalent properties and traits, but through the process of acting and network formation, positing a situation through which humans may be compelled to act (Foth, 2009).
Bruno Latour’s Act Network Theory diagram; Source: https://lemonlimebrit-ters.files.wordpress.com/2014/08/screen-shot-2013-03-24-at-2-58-26-pm. png
Chapter 3: Case Studies: Projects and Tools
Tech companies flushing into the urban scene, utilizing their resources in biometrics, blockchain, AI, big data and cloud computing and development of various types of sensor technologies have become the new norm in urban development. For instance, in China, Ping An, Alibaba, Tencent and Huawei are leading smart city initiatives, with 500 participating cities throughout the country, operating under the name PATH.
The increasing power of data to make decisions in determining how we live our lives, how we engage, who talks to whom, and who is allowed to play – is moving from the digital world to the physical world, which has serious consequences for urban governance. In this section, I select three case study projects, covering diversity in scales, key players, levels of resolution and intervention.
3.1 Neighborhood Scale: Sidewalk Toronto, Quayside, Ontario
In 2015, Google reorganized its resources and interests as a conglomerate called Alphabet Inc. Under the umbrella of Alphabet, Sidewalk Labs was established as an urban innovation organization fitted by a suite of urban products, from highspeed broadband services, autonomous self-driving cars, to smart homes equipped with a myriad of sensors. This hybrid background gives it leverage and resources to integrate various streams of data collection and technologies from other parts of its parent company into urban interventions, signaling a role switch of tech conglomerates from mere service providers to designers and visionaries of the built environment. The Sidewalk Toronto Project is a joint effort by Waterfront Toronto and Sidewalk Labs to develop a tabula rasa mixed-use community on Toronto’s Eastern Waterfront, beginning with the creation of Quayside, claimed to be the “first city from the Internet up.” The corporation of Waterfront Toronto was created in 2001 to oversee and lead the renewal of Toronto’s waterfront. The process of transforming 2,000 acres of brownfield lands on the waterfront into “beautiful, sustainable mixed-used communities and dynamic public spaces,” includes the projected creation of 40,000 residential units, one million square meters of employment space and 300 hectares of parks and public spaces. Additionally, one of the stated goals of Waterfront Toronto is “delivering a leading edge city-building model that seeks to place Toronto at the forefront of global cities in the 21st century” (Waterfront Toronto, 2017). In March 2017, Waterfront Toronto issued an RFP to identify an innovation and funding partner Suite of Alphabet’s urban products. Source: URL: Urban Research Lab.
Collage by the author using Sidewalk Toronto RFP materials physical layers digital layer buildings mobility public realm infrastructure ubiquitous sensors/Wi-Fi ubiquitous sensors/Wi-Fi flexible loft-housing autonomous vehicles pedestrian-oriented streets
shared utilities, under-ground robot delivery
in the development of one of its neighborhoods, Quayside. The RFP’s conditions for selection focused on sustainability, resilience, affordable housing, transit, building innovation, and economic opportunity, with the ambition that ideas piloted at Quayside would be “brought to scale across the waterfront, replicated in neighborhoods throughout Toronto, and ideally, be adopted by cities around the world.” Unlike conventional planning negotiations where a planning service is awarded a contract from the city, Alphabet will instead pay the city $50 million to develop the land. Architect and New Media scholar T.F. Tierney from the University of Illinois Urbana Champaign uses “The Stack” as a theoretical framework to understand Sidewalk Toronto and the way “technology conscribes, shapes, and disciplines its users within the urban environment” (Tierney, 2019).
Tierney argues that Sidewalk Labs is colonizing the post-industrial city by transforming everyday life into a zone of alloyed consumption (consumption here being defined as the extraction, processing, and resale of information) (Yuval Nova Harari). One of the biggest critique Sidewalk Toronto has received is its lack of transparency and citizen engagement, and addressing issues of data privacy and ownership, especially during the first two years of the project’s conception.
Map of Toronto Eastern Waterfront development area. Source: Sidewalk Labs
Transport data management. Source: Sidewalk Labs
Building energy data management. Source: Sidewalk Labs
Water sources data management. Source: Sidewalk Labs
Data governance structure for urban data collected by Sidewalk Toronto. Image source: summary by author based on recent news on urban data governance by Sidewalk Labs (November, 2018)
3.2 City Scale: Songdo International Business Districts, Incheon, South Korea
Built from scratch on reclaimed land, Songdo
International Business District in Incheon, South Korea has been the poster child of Smart City, intended to house a community of multinational businessmen and investors and their expatriate workforce, and to track the flows of traffic, waste, crime and services in the city through e-government management and central command station monitor. Unlike Sidewalk Toronto where the city is treated as an urban laboratory, Songdo’s primary goal is to become a model
aerotropolis that connects to a key international airport and global players.
In the Songdo model, the “smart” label is a branding device which reassures investors that the SEZ is enhanced with the advanced information and communication infrastructure needed to facilitate modern global business practices. The SEZ is designed to stimulate international investment and participation in the global market economy, where 70% of its financial investments come from multinational corporations. The project intends to provide a replicable model which could be bought for $40 billion.
Although the Master Plan attempts to formulate the perfect balance between walkability, scale, amenities and quality of life by satisfying indices of performance to evaluate its success, more than a decade since its earliest inception, now less than a quarter full, with a mere 70,000 residents, described by hyperbolically as having “Chernobyl-like emptiness.” What has gone wrong with the development is that the “generic, inflexible, elitist and controlling” approach to design omits qualitative factors such as cultural vibrancy and community bonding.
Source: Dailymail (https://www.dailymail.co.uk/sciencetech/article-5553001/28-billion-project-dubbed-worlds-Smart-City-turned-Chernobyl-like-ghost-town.html)
3.3: National Scale: Estonia
At the national scale, the nation of Estonia combines both SEZ and urban laboratory, which is designed to support the Estonian Regional Development Strategy goals of environmental sustainability and international economic competitiveness. Contrary to previous case studies, Estonia’s e-governance and e-services emphasizes on public participation. The governance structure ensures data privacy and trust, which allows ICT to become a key building block of national branding and citizen participation.
Estonia cyber security innovation (https://e-estonia.com/wp-content/ uploads/x-road-1024x609.jpg)
3.4 An Inventory of Digital Participatory Methods, Research and Tools
The concept of collaborative and participatory planning through data-driven means has been keenly explored by and championed by university research labs in the last five years as result of widespread of machine learning algorithms and ubiquitous computing of big data. The following examples are precedents that serve as an inventory of recent tools and technologies that have been developed and deployed to facilitate civic participation in the digital world.
City Matrix, Augmentation, and AI-assisted Decision Making Platform
MIT Media Lab’s City Science Group (formerly called Changing Places) led by Professor Kent Larson, sits at the forefront of developing and testing responsive platform and tools that could lead to more robust decision-making process in city planning. The lab’s flagship project “The CityMatrix” is such an example of a decision support system that utilizes an intuitive Tangible User Interface (TUI) that creates real-time feedback of multi-objective urban performances to help both experts and nonexperts evaluate their decisions, intending to expedite the rapid prototyping planning process in a collaborative setting (Zhang, 2017). Using a shallow three-layer convolutional neural network (CNN), the system produces predictions based on real-time input of the user. In this case, the agency of data and technology exists in the form of machine intelligence, which is intended to work hand in hand with human intelligence in the planning process, under the hypothesis that decision quality could be improved by the organic combination of both human and machine agency. This research has made major steps in contributions to evidence-based democratic decision making, real-time simulation prediction and optimization suggestion (Zhang, 2018). The physical setup of “The CityMatrix” consists of an Augmented Reality interface with live digital projection overlain onto a physical model of a generic urban block composed of optically
Tangible User Interface: augmented reality assisted urban visualization and decision making; Source: Media Lab City Science
Visual Computing
Although mixed and augmented reality provides an interactive and hands-on participation environment for multiple stakeholders, its limited outreach prevents the work to be intervened by a larger group of users. Instead, interactive mapping using Web interfaces offers an alternative way to display information and collect user input. Works by MIT’s Civic Data Design Lab in the Department of Urban Studies and Planning led by Associate Professor Sarah Williams exemplify how spatial analytics and geographic data visualization can be employed to highlight overlooked urban phenomena and to educate new audiences. An MIT thesis project “Painting with Data: From a Computational History of Urban Models to an Alternative Urban Computing” by SMArchS Computation student Carlos E.S. Olascoaga developed as part of lab research explores potentials of urban computing tools that integrates personal perception, cognition and notation in an open-source web-application to motivate civic engagement in policy making (Olascoaga, 2016).
CityEngine
Meanwhile, tools for collecting crowdsourced input at a larger scale have been explored by both industry and academia. CityEngine, an advanced 3D City Design software developed by Esri, incorporates a crowd-sourcing forum component in a Webviewer where individual opinions are collected and tagged onto 3D models of a design proposal to provide public feedback for the designer. Similar endeavors of seeking large-scale crowdsourced input using techniques in citizen science to foster community involvement around issues of risk driven urban research.
Crowdsourced Emergency Mapping
What we can speculate from these shifting ways and resilience can be found in MIT Urban Risk Lab’s Urban Risk Map project. The lab has developed a digital platform for both smartphone app and web that connects residents from parts of Indonesia, India and U.S. to emergency managers for efficient live data reporting and sharing during events of flooding. The platform has been used by over 300,000 residents during the high-intensity rainfall event in Jakarta on February 21, 2017, who have provided localized input Painting with Data: Carlos E.S. Olascoaga
Urban Risk Map by Urban Risk Lab Source: ESRI
Urban Simulation: UrbanSim
Developed by researchers from Berkeley as part of the Urban Data Science Toolkit, UrbanSim allows users to run simulations, which draws from a library of open data, and produces visualizations.
UrbanSIM interface, UC Berkley
Online platform: Neighborland
Neighborland is a public engagement platform designed for government agencies, developers, and civic organizations (Neighborland). The platform is designed for planners to collaborate with their stakeholders in an accessible, participatory, and equitable way. Over 3 million people have participated on Neighborland, and projects using the platform have yielded over $3 billion in social and economic impact.
existing online engagement tools involving participation of citizens at various stages; Source: Data Smart City Solutions, Harvard University
sensor: air quality sensor goal: mapping pollution senses: air pollution
sensor: thermometer goal: adjusting thermal comfort senses: temperature
sensor: 3axis accelerometer goal: track where people go senses: acceleration due to gravity
sensor: GPS
goal: track where people are going senses: location and trails of users sensor: LiDAR
goal: object detection senses: object point cloud sensor: motion sensor goal: activate another function senses: moving objects sensor: pressure plate goal: track vehicle speed senses: air pollution
sensor: smoke detector goal: hazard preventions senses: presence of smoke
sensor: sound sensor goal: assess activity levels senses: volume and noise sensor: ambient light goal: to assess light senses: light levels
sensor: camera
goal: traffic monitor, facial recognition senses: de-identified images
sensor: bin level sensor goal: efficient trash management senses: fullness of trashbins
sensor: infrared occupancy sensor goal: assess activity level
senses: passing pedestrians/cyclists sensor: bluetooth sensor
goal: broadcasting data
Chapter 4: Collective and Individual Data
A Taxonomy of Sensing Technologies and Data Collection
The following matrices summarizes an inventory of sensors currently found in the built environment, studies their data usage.
Urban Data (collective)
This section shows a catalog of sensors passively collecting information from the environment. Each row describes a sensor technology, the type of information it collects, and its usage in urban analysis. Environmental data captured are often used to further optimize infrastructural performance, management and efficiency.
Personal Data (individual)
Personal data include personal opinions, emotions and perceptions expressed by individuals on social media or public web platforms. They typically provide feedback for designers and policy makers to assess individual needs.
Tools and methods Summary
This section synthesizes digital participatory tools discussed in the previous chapter, discusses the benefits and challenges faced by each technology.
Chapter 5: A Framework Proposal
The way we currently research and understand a place could be quite superficial, based on many preconceived assumptions made from secondary sources, or brief one-time site visits. Traditional community engagement meetings and workshops take place to keep the general public informed, but they typically are limited to a small group of people, and often leave it at that, especially in Asia.
This thesis proposes an alternative design process using digital tools which facilitates continuous conversation between end-users with other official stakeholders, and designed a system and tool which could interface between designers and end-users throughout different phases of a project.
This work contributes to the efforts in the design field which have aimed to develop systems that facilitate digital participatory processes between designers and end-users. While most of these examples exist in black
USER
ENVIRONMENT
INPUT
(Objective
and subjective data)
INPUT
(Objective data
collected by sensors)
OPEN SOURCE INTERFACE
OUTPUT
(Adjusted
output based on feed
-back) OUTPUT (Intervention based on negotiations) An opensource interface mediated by the designer; cross-validates multiple sets of objective and subjective data to reach insights and box environments, this thesis proposes to create an open-source interface mediated by the designer to allow design to happen iteratively between different agencies based on constant user feedback.
Chapter 6: Design Speculation: Ang Sila, Chonburi, Thailand
The site is a 35-acre vacant land located in the touristic province of Chonburi, which is currently seeking novel IoT infrastructural initiatives to engage with the local context. The plot itself is adjacent to one of the oldest historical fishing village neighborhoods in Thailand and rich ecological feature of mangrove forests. I am interested to see how cities with rooted historical and environmental contexts evolve and adapt to welcome changes, where negotiating and working with local context is crucial.
BANGKOK
1.5 hr 91 km
ANG SILA HISTORIC FISHING MARKET PRATTHANA HOUSING SITE SHRIMP FARM MANGROVE FOREST OCEAN ROAD CLAM FARMS
As Chonburi develops in tourism, the challenge lies in preserving vernacular culture and strong ecological features on the site while accommodating new needs of incoming tourists. Ang Sila’s unique fishing village culture and mangrove forests are two most valuable local features under the threat of generic touristic development. local markets: souvenir shops
fishing village: extended piers
man-Moo 4 merchant street
Project site current condition
Fieldwork Research Mar 21-24, 2019
In March 2019, I have had the chance to go to Thailand and visit the site, where I was fortunate enough to be taken around by the local architect to meet with some of the residents, visit their homes, speak with environmental specialists and discuss ideas with the developer.
Local fishermen business
Local typology: jellyfish house
Local shrine in Moo 4.
Public space in shared spaces in the neighborhood
Local merchant LOCAL
priorities
reward
potential
opportunities
affecting business
performance
needs will be
considered in designs
Demographics on the site can be generalized into five types of user groups:
(1) the local Ang Sila merchant (such as fishermen and vendors who sell local crafts primarily concerned with business opportunities and locality preservation (2) the local repeat clientele: middle-class living in gated communities in surrounding neighborhoods with few options for leisure
Local repeat clientele
potential routine
reward
coupon and
discounts at
(3) the environmentalist who is concerned with ecological preservation and public education;
(4) the Out-of-Town Thai usually coming from Bangkok to seek a relaxing weekend stay
(5) the foreign tourist seeking adventure and fun: these range from budget college student traveler, to retired foreign tourist seeking a resort vacation, to digital nomads intending to stay for longer periods of time.
Environmentalist Out-of-town Thai Foreign tourist
NON-LOCAL
fun and
entertainment
entertainment
fun and
disseminate knowledge
and affect environmental
Cast of Characters
Based on this, I have created a cast of characters, with various age groups, marital status, income bracket and diverse mix of interests and goals. The variety of characters and unique site conditions of Ang Sila provides complex enough of a situation where I can evaluate how design and development can benefit from negotiating the voices of different perspectives.
Prim, 41-55, F
Environmentalist/mangrove enthusiast
Married | Family size: 3 | Language: Thai, English Priorities
Educate the public, ecological wellness, locality preservation, job opportunity
Spatial needs
Education center attracting various groups of people
Arthit, 26-30, M
Local merchant
Single | Language: Thai Priorities
Job opportunity Spatial needs Accessibility to work
Patti, 31-35, F
Local merchant
Married | Family size: 5 | Language: Thai Priorities
Open a new restaurant and live here Spatial needs
Requires “commercial + residential hybrid” mixed-use
Anong, 41-45, M
Local merchant
Married | Family size: 6 | Language: Thai Priorities
Expand business, vendor profit
Chaiya, 41-55, M
Local repeat clientele
Married | Family size: 5 | Language: Thai, English Priorities
Natural/open air with family (kids/elderly) Spatial needs
Accommodates kids, elderly, dogs, open space
Ping, 26-30, F
Out-of-town Thai vacationer Single | Language: Thai/English Priorities
Weekend getaway, relaxation, design preferences, locaity preservation
Spatial needs
Interesting spatial features, cares a lot about
non-gener-Nang, 56-65, F
Local merchant
Married | Family size: 4 | Language: Thai/Chinese Priorities
Weekend sell at market, commute convenience Spatial needs
Only comes during weekends
Pom, 26-30 M
Local repeat clientele Single | Language: Thai Priorities
Nice place to work and hangout, design preferences Spatial needs
Co-working space next to recreational areas and amenities; not near the fishing market
Asnee, 31-35, M
Out-of-town Thai vacationer
Married | Family size: 4 | Language: Thai/Chinese Priorities
Family activities, seeks vacation
Malee, 21-25, F
Local repeat clientele
Single | Language: Thai/Chinese Priorities
Entertainment, recreation activities Spatial needs
Nothing particular
Local merchant
Local repeat clientele
Nicole, 31-35, F
Foreign tourist
Married | Family size: 3 | language: Russian/English Priorities
Nature/leisure/local experience Spatial needs
Wants a view out into the ocean
Jonathan, 60+, M
Foreign tourist
Married | Family size: 5 | Language: English Priorities
Authentic local cuisine, seeks vacation Spatial needs
A luxurious resort overlooking the ocean
Bom, 26-30, M
Out-of-town Thai vacationer
Married | Family size: 2 | Language: Thai/Chinese Priorities
Unique experiences, design preferences Spatial needs
Yiwei, 26-30 F
Foreign tourist
Single | Language: Chinese/English Priorities
Fun/adventure seeking, locality preservation Spatial needs
Would like to stay in a hostel rather than a fancy hotel
Ian, 31-35, M
Foreign digital nomad
Single | Language: English/elementary-level Thai Priorities
Comfortable working space, nice and clean environment,
Chantara, 19-25, F
Out-of-town Thai vacationer Single | Language: Thai Priorities
Local cuisine and fun experience with friends Spatial needs
Parking space
Against this context, the goal is to create programs and spaces that could accommodate and negotiate different needs and integrate local narratives, habits, and cultures into newly developed tourism. How can we take the civic space and cultivate civic learning, where we add within these various participatory actions through multiple nodes of connections during the design and development process?
Chapter 7: Design of Tool
Using my proposed design process and tool which I call CoDAS (Co-Design Ang Sila), I will run the design process as a continuous conversation between different stakeholders, from pre-design/planning all the way to post-occupancy. Consisting of both digital and physical components, the tool creates an interface between developers, designers and citizens, and invite contributions from large amounts of audience on the site. It is a means to create an emotional census of Ang Sila neighborhoods and a digital overlay of the city’s personal narratives and perceptions, providing granular neighborhood insights which assist with design
decision-making.
Initially, several information objects are introduced to key public spaces (such as Pun Tao Kung Ma Shrine, Seafood Market, the Royal Forest Office) on site to begin informing the public about the development project and CoDAS initiative. These physical stations, depending on available funding and significance, can exist as a standalone pavilion, a kiosk inside a public building such as a library, or simply an urban furniture with ingrained information. These are anchored on site where you can continue to stay informed and get information, for visitors or people who are not digitally connected.
Taking advantage of existing social media, the CoDAS incentivizes participation and data contribution from the bottom-up. In Thailand, 92% of connected consumers use an app called Line (the Southeast Asian WhatsApp) where people organize their online social life. Citizens connect with the CoDAS by adding a Line Chatbot, and receives a notification whenever a question is deployed or an announcement is made, to stay virtually connected with the project during each stage.
Physical
Digital
Existing uses/local culture
New
programs
Built form
Physical installation
Target image
Visualization
Social network
Crowdsourced opinion
and perceptions
Experience sharing
pavilion cafe/library table with gamified
interactive display urban furniture graffiti wall
projection onto a physical model
Scan and map your feedback!
Hi! Thanks for adding me. Please help me answer a few questions.
Sure!
CDB ANGSILA
aerial/plan view
streetview/walkthrough
for me I love this place because... timeline filter by: design question: images/videos/audiostext demographics analysis upload
I want to answer the question
CoDAS
Pun Tao Kong Ma Shrine
Ang Sila Pittayakhom School
Seafood Market
Isan Kobori Sangdaw
Chao Mae Kuan Im Shrine
Ang Sila Coffee & Bistro Local Restaurant Chonburi Royal Forest Office
Local Restaurant
pavilion cafe/library table with gamified interactive display urban furniture graffiti wall
projection onto a physical model
Pun Tao Kong Ma Shrine
Ang Sila Pittayakhom School
Seafood Market
Isan Kobori Sangdaw
Chao Mae Kuan Im Shrine
Local Restaurant
Ang Sila Coffee & Bistro
Local Restaurant
Access with your Line account Adds “CODAS” Chatbot User Group
Hi! Thanks for adding me. Please help me answer a few questions.
Sure!
CoDAS
Foreign tourists
Out-of-town Thai vacationers Local repeat clientele
identify user group through survey
Chapter 8: Deployment on Site
For the design portion of the thesis, I have run through a hypothetical development process on the site which demonstrates various use cases to see how this process and tool can be deployed and become beneficial throughout different phases. The user experiences the feedback process mostly through the mobile end in Line Chat, where they receive questions and respond to give their input, which could be in the form of text, images/videos, and votes. The open-source web platform geospatially locates the crowd-sourced information and visualizes key information for the designer, and tracks changes of the designed project overtime. Depending on the nature of the question, each data collection period has a different expiration date.
When the user initially connects with the CoDAS Line Chatbot, they get a message that briefly introduces the project and goals of the data collection. Any additional information could be accessed on the web. Users then receive a quick survey, which asks about their locality, frequency of visit, age bracket and family size, and classifies them as one of the five categories introduced in the previous chapter.
Initial Registration
CoDAS Chatbot: “Hi, I am the CoDAS Chatbot. Thank you for adding me as your friend! The ASL Development is a multi-use project which aims to combine new tourism, historical Ang Sila fishing village culture, and the unique ecological characteristics of the region. We will be asking you for your opinions throughout the development phase so you can be part of designing and improving the project for Ang Sila and get recognized for your feedback. Please visit www. codesignangsila.com for more information and to see what others have said! You can use your Line account to login to input information.”
“But first of all, please answer a few questions so we can get to know you better! All your information will be denonymized.”
“Are you from Ang Sila?”
“If so, do you own a business here?” “If not, how often do you come to Chonburi?”
“Please select from below as
your age bracket: REPLY 1 for below 19 years old, 2 for 19-25 years, 3 for 26-30 years, 4 for 31-35 years, 5 for 36-40 years, 6 for 41-50 years, 7 for 51-60 years and 8 for 60+ years.”
“What language do you speak?” “How many people do you live with?”
“Do you live with anyone under 18 years old or above 60 years old?”
Web Interface
This information is mapped onto the web interface, displaying geospatially distribution of interest from different user groups. The web portal of the program contains more comprehensive information about the project and allows users to access updates about the project at all given times.
The web dashboard keeps a tally of total number of people participating, allows filtering of information based on different group and age bracket, displays the phasing of the project, allows the browsing of other survey questions; and shows highlights and insights of the collected data such as key words, sentiment analysis
RESEARCH AND PLANNING PHASE
During the research phase, a question is deployed to gather information about existing “hot spots” to gain local insights on preferences and existing habits. A small reward system motivates the user to contribute their input.
CoDAS Chatbot: “What is your favorite place to hang out in Ang Sila? What do you do on the weekends? Share with us a photo of your favorite place for a chance to get your picture featured on our website as the “Best Picture of Ang Sila.”
Nang: “the hangout spot on the sidewalk outside Moo4. We play cards!”
Asnee: “Sitting by the pier overlooking the sunset.”
Chaiya: “I go to Thepsathit Phra Kiti Chalerm Chinese Shrine every weekend with my wife to do our prayers.” Anong: “Hanging out with my neighbors outside of our houses, with all the kids running around”
Pom: “I love the Austin Café.”
This scenario shows how we can use crowdsourced information to map and understand local perception of existing public spaces.
Anong Chaiya Pom Nang Asnee CoDAS
DEVELOPMENT PHASE I AND PHASE II: REFORESTATION AND REPLANTING OF MANGROVES
CoDAS can also serve to broadcast a community activity opportunity and recruit members of the community to participate in physical building.
CoDAS Chatbot: “During Phase I and Phase II of the development, we will be introducing ecological restoration to bring back natural beauty back on site. Did you know that the Ang Sila region is rich in mangrove population which protects the shoreline from damaging storms and hurricane winds, waves and floods? The ASL Development Phase II will replant the mangroves along the coast and we need your help! Reply YES if you would like to sign up for the Mangrove Forest Restoration and Conservation project.”
Malee: “That sounds like fun! Yes.”
CoDAS Chatbot: “120 people from the community have helped last weekend with the replanting endeavor. Join us this week to help your community!”
Chaiya: “I think my kids will enjoy this.”
As a result, Ang Sila locals join forces to be part of mangrove reforestation, an activity which is documented and further promoted on the web.
CoDAS
Chaiya CoDAS Malee
Chaiya Malee
