The Spangen neighborhood in Rotterdam West, the Netherlands, is highly vulnerable to pluvial flooding due to its low elevation, numerous impervious surfaces, and proximity to the Delfshavense Schie canal and a surrounding feeder canal. These factors contribute to high local surface runoff and strain on the local combined sewer system (CSS), leading to combined sewer overflows (CSOs) and local street fooding (“water op straat”). This study investigates the potential of integrating blue-green infrastructure (BGI) together with real-time control (RTC) to mitigate flood risk by reducing both the volume and frequency of CSOs and swale overflow events. A hydrological model, built utilizing 20 years of meteorological data with a 10-minute resolution from November 01, 2004 to October 01, 2024, simulated the hydrological effects of three progressively integrated bioswale configurations, a baseline scenario, and further modeled the effectiveness of RTC as valves outfitted at the base of the swale overflow tructure in preemptively releasing forecasted runoff over a 12-hour lead time. Results demonstrated that while the baseline scenario revealed 582.5 mm of CSO overflow over 188 events during the study period, when implemented, bioswales alone reduced net flow to the receiving water body by up to 95%, and RTC-enabled bioswales, in the most intensive configuration, could fully, pre-emptively remove stored swale volume to completely eliminate uncontrolled overflow. The 25% interception fraction performed best for Configuration 1, and 50% fraction performed best for Configurations 2 and 3, which all minimized the net flow out to the receiving water body, most efficiently integrating the existing CSS and proposed bioswales. Beyond mitigating flood risks, BGI offer co-benefits such as enhanced ecological connectivity, improved water quality, and urban livability, serving as a tool to provide Gemeente Rotterdam with a new possibility to achieve other sustainability goals, such as increasing green space access. This research demonstrates that the integration of RTC with BGI can serve as a scalable model for climate-resilient urban water management in Rotterdam, and worldwide.

This study addresses the critical question: How can AI be effectively harnessed to serve humanity’s global well-being? Referencing Barber’s (1998) dilemma, we ask whether AI will lead us toward a Pandora scenario—marked by chaos and harm—or a Jeffersonian scenario, where AI fosters democratic opportunities. To explore this, we developed a citizen-friendly AI prototype focused on road safety, an urgent global challenge with 1.19 million fatalities annually, particularly in low- and middle-income countries, according to the World Health Organization.

Our AI-co-created website, utilizing Generative AI as an assistant, aims to disseminate proven road safety strategies, such as “Sustainable Safety” and the “Urban Street Design Guide,” which have been successfully implemented in the Netherlands and various U.S. cities. The prototype seeks to bridge language and knowledge gaps, empowering citizens worldwide with accessible road safety insights.

Employing the Prototype Method, this study underwent three development iterations, integrating feedback from diverse citizen groups through workshops and surveys. The final product, prototype 3, presented in a semi-manual, semi-AI format, demonstrates that AI can significantly enhance civic participation and public affairs.

Based on the Human-Centered AI (HCAI) framework, we introduce an advanced "Citizen-AI" model, incorporating the ARIE evaluation model—Avoid, Reduce, Insist, Encourage—to ensure ethical AI deployment. Together with the 3E framework: Education, Empowerment, and Engagement, the ARIE model offers a comprehensive self-assessment tool for developers, guiding the creation of AI systems that prioritize human welfare. This study envisions a future where citizens are equipped to use AI as an active tool for participation, bridging the gap between technology and public engagement.