NetZeroCities

City Dashboards are typically deployed by stakeholders such as municipalities, provinces or any other organization interested and involved in urban planning. Dashboards provide cities with visual insights about various indicators in their city environment, such as air quality, emissions, traffic, and road safety. These insights can be generated in real-time, based on different current, as well as historical, data that has been collected in the past. Examples of such data can be real-time sensor data which can be provided by IoT sensors owned by inhabitants or by a municipality, road authority, etc. (e.g., air quality sensors) and by sensors that are part of the road infrastructure, such as loop detectors that count traffic. Dashboards provide stakeholders with clear visual support, in the decision-making processes for steering towards their climate neutrality goals, and can be used as a quick, clear and tangible tool to provide a good overview of the KPIs of interest in a city. They enable the various stakeholders to quickly inspect the current situation in a city and use these insights during the urban planning process. For example, energy companies and power grid operators may be interested in KPIs related to e.g., demand for electric vehicle charging. Further, emissions can indicate critical parts of the network that require attention, while potential improvements after implementation of specific measures can be monitored easily. Individual KPIs, if desired, can be presented in different forms, such as tables, charts, graphs, text etc., other than maps. In addition to visualization of KPIs, a dashboard can also show in which areas only a few sensors are installed, which means that it can indicate in which areas it may be beneficial to deploy additional sensors to get a better overview and monitoring of the city.

Dashboards can assist stakeholders in several domains, which can result in a better living environment of citizens. On top of that, via citizen participation actions, citizens can be involved in getting awareness of their city conditions, as well as in participating in the decision-making processes.

Figure 1: Inspecting noise levels in Amsterdam using a dashboard (source: TNO)

Technical:

Visualization of privacy sensitive data is typically challenging. For example, getting detailed insights on traffic accidents requires accident data, but typically this data is aggregated to prevent that individuals in a dataset can be identified. Similar challenges arise in the context of Mobility-as-a-Service. Getting detailed insights on travel behavior requires information about individual trips, but service providers may not be allowed to share data which describes individual trips. There are multiple solution directions that can be explored to deal with privacy sensitive data. First, multiple parties may enter a consortium in which contracts are established describing how data may be used. Second, it may be possible to pre-process existing data such that data belonging to individuals cannot be identified in the resulting dataset. Finally, new machine learning techniques such as federated learning may be used to extract insights from multiple separate datasets, without revealing the original data.

Funding and financing:

Initiation of a project normally by the municipality or other stakeholder who owns the data and requires the dashboard from an expert who could be a research institute, a university, a consultancy, etc.

Social:

In the LocalRES project citizens were not comfortable with seeing data in maps, while others were comfortable. Citizen workshops made very clear that community supporting tools need to be adapted both to the specific requirements of the participating town as well as to the needs of the individual end users. The development of community tools needs to consider the varying degree of technical literacy [1]. Different options of visualization might be needed depending on the end-user (For experts-->maps, for citizens a possibility to visualize their data by searching by address instead of a map and showing big numbers with a narrative).

[1] https://open-research-europe.ec.europa.eu/articles/2-129

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