Paper Type
Complete
Paper Number
PACIS2026-1957
Description
Urban health monitoring systems systematically fail to detect emerging compound risks because they treat data as passive measurements of objective conditions rather than as expressions of collective meaning-making. We term this the expression mechanism gap and address it through a design science research approach. Drawing on symbolic interactionism and phenomenology, we develop the Signification Detection Framework — a mid-range design theory comprising five design principles that govern how anticipatory urban health monitoring systems should be built. We instantiate these principles in CityScan, a system deployed by Singapore's Ministry of National Development since 2023 across 55 planning areas. CityScan integrates behavioral data across five phenomenological dimensions — Sociality, Embodiment, Meaning, Materiality, and Spatiality — through a multi-algorithm ensemble that detects cross-dimensional convergences invisible to single-agency monitoring. Evaluation demonstrates that CityScan surfaces compound health vulnerabilities, including a dementia risk cluster in western Singapore, that are structurally undetectable by traditional measurement-based systems.
Recommended Citation
Hu, Zhichao; Goh, Kim Huat; and Boh, Waifong, "From Measurement to Signification: A Design Theory for Anticipatory Urban Health Monitoring Systems" (2026). PACIS 2026 Proceedings. 12.
https://aisel.aisnet.org/pacis2026/iot_smartcity/iot_smartcity/12
From Measurement to Signification: A Design Theory for Anticipatory Urban Health Monitoring Systems
Urban health monitoring systems systematically fail to detect emerging compound risks because they treat data as passive measurements of objective conditions rather than as expressions of collective meaning-making. We term this the expression mechanism gap and address it through a design science research approach. Drawing on symbolic interactionism and phenomenology, we develop the Signification Detection Framework — a mid-range design theory comprising five design principles that govern how anticipatory urban health monitoring systems should be built. We instantiate these principles in CityScan, a system deployed by Singapore's Ministry of National Development since 2023 across 55 planning areas. CityScan integrates behavioral data across five phenomenological dimensions — Sociality, Embodiment, Meaning, Materiality, and Spatiality — through a multi-algorithm ensemble that detects cross-dimensional convergences invisible to single-agency monitoring. Evaluation demonstrates that CityScan surfaces compound health vulnerabilities, including a dementia risk cluster in western Singapore, that are structurally undetectable by traditional measurement-based systems.
Comments
10-IoT