Band 20, Heft 2 - Special Issue "E-Government and Smart Cities"

Data acquisition is a central task in research and one of the largest opportunities for citizen science. Especially in urban surveys investigating traffic and people flows, extensive manual labor is required, occasionally augmented by smartphones. We present DesPat, an app designed to turn a wide range of low-cost Android phones into a privacy-respecting camera-based pedestrian tracking tool to automatize data collection. This data can then be used to analyze pedestrian traffic patterns in general, and identify crowd hotspots and bottlenecks, which are particularly relevant in light of the recent COVID-19 pandemic. All image analysis is done locally on the device through a convolutional neural network, thereby avoiding any privacy concerns or legal issues regarding video surveillance. We show example heatmap visualizations from deployments of our prototype in urban areas and compare performance data for a variety of phones to discuss suitability of on-device object detection for our usecase of pedestrian data collection.

In this paper, we argue for and present an empirical study of putting citizens into focus during the early stages of designing tools for civic participation in a mid-sized German town. Drawing on Contextual and Participatory Design, we involved 105 participants by conducting interviews, using Photovoice and participating in a local neighbourhood meeting. Together with citizens, we built an Affinity Diagram, consolidated the data and identified key insights. As a result, we present and discuss different participation identities such as Motivated Activists, Convenience Participants or Companions and a collection of citizen needs for local civic participation, e. g., personal contact is irreplaceable for motivation, trust and mutual understanding, and some citizens preferred to “stumble across” information rather than actively searching for it. We use existing participation tools to demonstrate how individual needs could be addressed. Finally, we apply our insights to an example in our local context. We conclude that if we want to build digital tools that go beyond tokenistic, top-down ways of civic participation and that treat citizens as one homogeneous group, citizens need to be part of the design process right from the start. Supplemental material can be retrieved from https://osf.io/rxd7h/.

Smart cities aim at improving efficiency while providing safety and security by merging conventional infrastructures with information and communication technology. One strategy for mitigating hazardous situations and improving the overall resilience of the system is to involve citizens. For instance, smart grids involve prosumers —capable of producing and consuming electricity—who can adjust their electricity profile dynamically (i. e., decrease or increase electricity consumption), or use their local production to supply electricity to the grid. This mitigates the impact of peak consumption periods on the grid and makes it easier for operators to control the grid. This involvement of prosumers is accompanied by numerous socio-technical challenges, including motivating citizens to contribute by adjusting their electricity consumption to the requirements of the energy grid. Towards this end, this work investigates motivational strategies and tools, including nudging, persuasive technologies, and incentives, that can be leveraged to increase the motivation of citizens. We discuss long-term and side effects and ethical and privacy considerations, before portraying bug bounty programs, gamification and apps as technologies and strategies to communicate the motivational strategies to citizens.

Smart cities have a huge potential to increase the everyday efficiency of cities, but also to increase preparation and resilience in case of natural disasters. Especially for disasters which are somewhat predicable like floods, sensor data can be used to provide citizens with up-to-date, personalized and location-specific information (street or even house level resolution). This information allows citizens to better prepare to avert water damage to their property, reduce the needed government support, and — by connecting citizens locally — improve mutual support among neighbors. But how can a smart city application be designed that is both usable and able to function during disaster conditions? Which smart city information can be used? How can the likelihood of mutual, local support be increased? In this practice report, we present the human-centered development process of an app to use Smart City data to better prepare citizens for floods and improve their mutual support during disasters as a case study to answer these questions.