Paper presentations Virtual Room
Feb 17, 2022 01:30 PM - 03:00 PM(Europe/Amsterdam)
20220217T1330 20220217T1500 Europe/Amsterdam Responsible Urban Digitization Virtual Room Reinventing the City events@ams-institute.org
37 attendees saved this session
To ensure smooth communication and collaboration, here are some troubleshooting tips to address common issues:
  1. Check Internet Connection: Verify that you have a stable and reliable internet connection. Use a wired connection when possible, as it tends to be more stable than Wi-Fi. If using Wi-Fi, make sure you have a strong signal.
  2. Update the Browser or App: Ensure that you are using the latest version of the web browser. Developers frequently release updates to address bugs and improve performance.
  3. Clear Browser Cache: Sometimes, cached data can cause conflicts or issues. Clear the browser cache and cookies before joining the meeting.
  4. Test Audio and Video: Before the meeting, check your microphone and camera to ensure they are working correctly. If you are a speaker, you can click on "Start Practice Session" button test to ensure audio and video devices are functioning.
  5. Close Other Applications: Running multiple applications in the background can consume system resources and lead to performance issues. Close unnecessary apps to free up resources for the Dryfta meeting platform.
  6. Restart Your Device: If you encounter persistent issues, try restarting your computer or mobile device. This can help resolve various software-related problems.
  7. Use Supported Browsers: Ensure you are using a browser supported by the meeting platform. Recommended browsers: Chrome, Firefox, Edge, and Brave.
  8. Allow Necessary Permissions: Make sure the Dryfta meeting platform has the required permissions to access your microphone, camera, and other necessary features.
  9. Disable VPN or Firewall: Sometimes, VPNs or firewalls can interfere with the connection to the meeting platform. Temporarily disable them and see if the issue persists.
  10. Switch Devices: If possible, try joining the meeting from a different device to see if the problem is specific to one device.
  11. Reduce Bandwidth Usage: In cases of slow or unstable internet connections, ask participants to disable video or share video selectively to reduce bandwidth consumption.
  12. Update Drivers and Software: Ensure your operating system, audio drivers, and video drivers are up to date. Outdated drivers can cause compatibility issues with the Dryfta meeting platform.
  13. Contact Support: If none of the above steps resolve the issue, reach out to the platform's support team. They can provide personalized assistance and troubleshoot specific problems.
By following these troubleshooting tips, you can tackle many common problems encountered on Dryfta meeting platform and have a more productive and seamless meeting experience.
A Web-based Tool to Support Human-Centered Design of Inclusive Urban InterventionsView Abstract
01:30 PM - 03:00 PM (Europe/Amsterdam) 2022/02/17 12:30:00 UTC - 2022/02/17 14:00:00 UTC
Brainstorming ideas of solutions to urban societal problems is complex since it requires including the perspective of diverse stakeholders with unique needs and values at a large scale. Applying participatory design approaches can center on people's perspectives but suffer from scalability problems. In addition, participatory design usually relies on policymakers' experiences in integrating diverse perspectives at a small scale. There is a lack of digital tools that can support policymakers in doing so at a large scale. In response to this challenge, we are developing a web-based tool to crowdsource opinions collection for large-scale design policymaking, such as COVID-19 measures. Also, based on previous work, we identify empathy as a crucial factor in engaging people in ideation at a small scale, such as design workshops. Building on this prior knowledge, we investigate how digital tools can augment empathy between different stakeholders to support large-scale ideation on pressing societal issues. We conducted user studies to understand the relationship between empathy, people's behaviors, and user interaction design. We recruited around 400 participants using a crowdsourcing platform (Prolific). Participants were asked to provide opinions on policies regarding smart working during the pandemic. Using our tool, they can look at other people's choices and motivations. They can also choose to change their opinion. We use the results (e.g., the user interaction design that led to a more balanced policy) to derive empirical design implications and discuss them in this presentation. Even though the results are for a specific use case, we believe they can be generalized to create more inclusive urban interventions.
Presenters
YH
Yen-Chia Hsu
TU Delft
Andrea Mauri
TU Delft
Safeguarding Machine Vision in Cities: Know What Your Machine Shouldn’t KnowView Abstract
Oral presentationResponsible Urban Digitization 01:30 PM - 03:00 PM (Europe/Amsterdam) 2022/02/17 12:30:00 UTC - 2022/02/17 14:00:00 UTC
Machine vision systems are increasingly used for smart city applications such as infrastructure condition monitoring, vehicle compliance detection, etc. While facilitating fast decision-making at scale, these systems can be easily repurposed for unaccounted usages that are potentially harmful to stakeholders. To restrict the usage of such systems, it is important to draw a clear boundary of what they are capable of doing and safeguarding the system for only intended usages. The challenge however comes in two folds: 1) state-of-the-art machine vision systems are black-boxes whose behaviors are unintelligible to humans, 2) it’s often unclear what the system should be knowing, which is essential for limiting system usage. This project aims to develop human-in-the-loop methods and tools for understanding the capability of machine vision systems and safeguarding their usages. We consider humans both as the computational agents for interpreting machine behaviors and as the domain experts and stakeholders to create requirements of what a system should know. We also consider computational methods as vital tools to assist humans in the reasoning for what a system knows that goes beyond what it should know. As the outcome of the project, we envision the development of a rejection mechanism that can safely reject the output of machine vision systems when the system leverages input information that goes beyond its intended capability.
Presenters
XC
Xinyue Chen
Student, TU Delft
JY
Jie Yang
Assitant Professor, TU Delft
Andrea Mauri
TU Delft
Agent-based Modeling of Urban Exposome Interventions: Prospects, Methodological Considerations and ChallengesView Abstract
Oral presentationResponsible Urban Digitization 01:30 PM - 03:00 PM (Europe/Amsterdam) 2022/02/17 12:30:00 UTC - 2022/02/17 14:00:00 UTC
With ever more people living in cities worldwide, it becomes increasingly important to understand and improve the impact of the urban habitat on health behaviours and health outcomes. However, implementing interventions that tackle the Exposome in complex urban systems can be costly, has long-term impacts and can have unforeseen consequences. Hence, it is important to assess the health impact, cost-effectiveness and social distributional impacts of possible Urban Exposome Interventions (UEIs) before implementing them. Spatial Agent-based modeling (ABM) has the ability to capture complex behaviour-environment interactions, exposure dynamics and social outcomes in a spatial context. In this paper, we discuss methodological considerations and challenges for successfully modelling UEIs using Spatial ABM. We discuss the potential and limitations of the method; model components required to capture active and passive exposure and intervention effects; human-environment interactions and their integration into the macro-level health impact assessment and and a social costs benefit analysis. We also discuss strategies for model calibration. Major challenges for a successful application of ABM to UEI-assessment are (1) the design of a realistic behavioural model that is able to capture different types of exposure and that responds to urban interventions, (2) the mismatch between the possible granularity of exposure estimates and the evidence for corresponding exposure response functions, (3) the scalability issues that emerge when aiming to estimate long-term effects such as health and social impacts based on high-resolution models of human-environment interactions, (4) as well as the data- and computational complexity of calibrating the resulting ABM. This paper suggests possible strategies to addressing these challenges and provides a roadmap for further implementation of Spatial ABM in Urban Exposome Intervention Assessment.
Presenters Tabea Sonnenschein
PhD Candidate, Utrecht University
Co-Authors
SS
Simon Scheider
Utrecht University
AD
Ardine De Wit
Amsterdam UMC
RV
Roel Vermeulen
Utrecht University
A global analysis of multifaceted urbanization and implications for sustainability using Earth ObservationView Abstract
Oral presentationResponsible Urban Digitization 01:30 PM - 03:00 PM (Europe/Amsterdam) 2022/02/17 12:30:00 UTC - 2022/02/17 14:00:00 UTC
Urbanization as a global phenomenon is a multifaceted process, affecting the Sustainable Development Goals (SDGs) in and around urban areas. Here we do the first global attempt to characterize the complexity of urbanization from 1975 to 2015 in terms of population, built-up structure, and greenness, as well as monitoring urban sustainability indicators at the grid level covering all inhabited areas. We used Global Human Settlement Layer to assess built-up structure, population and land-use efficiency (SDG 11.3.1), combined MODIS/Terra & GIMMS NDVI for long-term greenness, distributed statistical energy consumption by night lights, and population for energy efficiency (SDG 7.3.1), and used near-surface PM2.5 dataset for air quality (SDG 11.6.2). Our results emphasize that the multifaceted nature of urbanization as well as related sustainable challenges vary greatly across regions and times. (1) Increased population density and built-up patch density was dominant in Asia and Africa, while urbanization in Europe and North America took a rather steady pace, combined with widespread greening. (2) According to the urbanization types identified by a self-organizing map (SOM) algorithm, a large proportion of urban and suburban areas experienced two dynamic urbanization types - built-up extension/leapfrog and built-up infill with large population increase (Fig. 1). (3) During different historical periods (1975-1990, 1990-2000, and 2000-2015), annual increases in population and built-up density were slowing coinciding with an increasing greenness – signaling that urbanization processes are becoming less intense, more compact, and “greener” over the most recent period. (4) Land-energy-air SDGs have declined in over 30% of global inhabited grid cells from 2000 to 2015. (5) In land-energy-air sustainability trends, urban areas perform relatively better than rural areas in the Global South, while urban areas in the Global North tend to be less sustainable than their surrounding rural regions. Our findings facilitate a comprehensive understanding of global urbanization and relevant sustainability with many local variations and characteristics. Integrating Earth Observation data is crucial for tracking urbanization and sustainability, and can guide context-specific strategies towards a sustainable and livable future instead of a ‘one-size-fits-all’ policy for cities.
Assitant Professor
,
TU Delft
Student
,
TU Delft
PhD Candidate
,
Utrecht University
AMS-Institute
AMS Institute
 Thomas Schönberger
Scientific Project Manager
,
German Federal Institute for Research on Building, Urban Affairs and Spatial Development
 Katharina Keienburg
Innovations Kontakt Stelle (IKS) Hamburg / Innovation Liason Center Hamburg
AMS Institute
+10 more attendees. View All
Upcoming Sessions
386 visits