A systematic review on the role of IoT and digital transformation in routine urine screening
A Systematic Review of IoT‑Enabled Digital Transformation in Routine Urine Screening
Routine urine screening is undergoing a major digital shift, driven by breakthroughs in IoT, AI, microfluidics, and cloud‑connected diagnostic systems. This systematic review compiles evidence from 65 studies published between 2000 and 2025, highlighting how IoT‑enabled urine screening now supports real‑time biomarker monitoring, faster diagnostics, and remote clinical decision‑making across diverse healthcare settings. These technologies address long‑standing challenges such as delayed reporting, dependence on centralized labs, limited access in rural areas, and the need for trained personnel ultimately enabling earlier detection of kidney disease, UTIs, diabetes, and metabolic disorders.
How IoT, AI, and Digital Health Technologies Are Transforming Urine Diagnostics
The review reveals how modern IoT‑based urine screening systems use optical sensors, electrochemical biosensing, microfluidics, acoustofluidics, BLE/Wi‑Fi connectivity, and AI‑driven analytics to deliver accurate, automated, and high‑frequency urine data. These advancements allow biomarkers such as protein, glucose, pH, nitrites, creatinine, and urinary cells to be monitored with precision in real‑time far beyond what traditional dipstick tests can achieve. By integrating with cloud platforms and edge computing, these systems enable decentralized diagnostics, seamless data sharing, and personalized healthcare pathways through emerging frameworks like digital health twins (HDTs). This evolution signals a shift from episodic lab testing to continuous, accessible, and patient‑centered urine monitoring, even in low‑resource environments.
