FluidCare: Automated Fluid Management In Healthcare Using IoT

This paper presented FLUIDCARE, a working prototype of a multi-tier IoT system for real-time hospital fluid-bag monitoring, with a production-oriented architecture; com-ponents remaining for deployment are enumerated in Sec-tion VIII. The four-tier architecture connects sensor nodes, a repeater mesh, and a master gateway through ESP-NOW, and bridges to the cloud via MQTT over TLS. A two-tier signal pipeline—on-device IQR-median filtering followed by server-side monotonic-depletion validation and EWMA smoothing—provides robust noise rejection for clinical envi-ronments. Calibration over 7,855 observations across 13 ref-erence masses confirms a linear sensor model (R2 = 0.9995, RMSE = 3.47 g, MAE = 2.87 g, both in-sample) with short- term repeatability of ±1–2 g (1σ) and absolute calibration accuracy of RMSE = 3.47 g. The 1 g change-detection threshold implemented in firmware is supported by the post-filter noise floor. Four prototype defects have been identified and described in Section VIII: light-load and above-range cal-ibration limitations, unimplemented blood/urine alert dispatch, the absence of a refill-detection mechanism, and the per-master scalability ceiling.

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