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Urban stormwater management is increasingly a challenge due to land use change, aging infrastructure, and climate‐driven precipitation variability. Likewise, maintaining regulatory compliance for stormwater permits is becoming more difficult. This study develops and deploys stormwater sensors using an Internet of Things‐based monitoring framework on the University of Maryland campus, a spatially compact but land use diverse testbed, designed to support both compliance and adaptive planning. Across three campus outfalls for stormwater quantity and quality data collection, the study investigates how hyperlocal precipitation and catchment characteristics affect stormwater flow and identifies key patterns in stormwater flow and quality through continuous monitoring. Findings reveal correlations between runoff behaviors and catchment characteristics (i.e., imperviousness) and highlight site‐specific associations between runoff flow and water quality indicators (pH, turbidity, conductivity, and dissolved oxygen). These associations can be leveraged as indicators of flood and pollution risk for management and planning purposes. This study also explores the role of campus stakeholders in guiding a “smart” system design, deployment, and big data use and outlines adaptive and preventive strategies for mitigating field deployment challenges and optimizing system performance that is a practical, compliance‐oriented model for smart stormwater monitoring in complex urban settings at various scales. 

Many children are growing up in a “digital-by-default” world, where technologies mediate many of their interactions. There is emerging consensus that those who design technology must support children’s privacy and security. However, privacy and security are complex concepts that are challenging to design for, and centering the interests of children is similarly difficult. Through a document analysis of 90 HCI publications, we examine what problems and solutions designing for children’s privacy and security addresses and how this research engages with children. Applying Solove’s privacy taxonomy, we find that research addresses a range of problems related to information collection, processing, dissemination, and invasion at the organizational, system, and individual levels. Children’s participation in this research is largely limited to providing feedback rather than helping to guide the research itself. Based on these findings, we offer recommendations for designers to sharpen their privacy and security contributions and center children in their work. 

Researchers and policymakers advocate teaching children about digital privacy, but privacy literacy has not been theorized for children. Drawing on interviews with 30 families, including 40 children, we analyze children’s perspectives on password management in three contexts—family life, friendship, and education—and develop a new approach to privacy literacy grounded in Nissenbaum’s contextual integrity framework. Contextual integrity equates privacy with appropriate flows of information, and we show how children’s perceptions of the appropriateness of disclosing a password varied across contexts. We explain why privacy literacy should focus on norms rather than rules and discuss how adults can use learning moments to strengthen children’s privacy literacy. We argue that equipping children to make privacy-related decisions serves them better than instructing them to follow privacy-related rules.