A systematic review on the role of IoT and digital transformation in routine urine screening

Background: Urine screening is a critical diagnostic tool in healthcare that supports the detection of a wide range of health conditions, including kidney diseases, metabolic disorders, and infections. Traditionally, urine tests are performed in clinical settings with results that often take time to be delivered. Such delays can hinder timely diagnosis, treatment initiation, and effective disease management. Recent advancements in digital health technologies, particularly the Internet of Things (IoT), machine learning (ML), and artificial intelligence (AI) algorithms, create opportunities for real-time data acquisition, integration, and analysis within routine urine screening. This systematic review synthesizes the current landscape of IoT-enabled urine screening technologies and evaluates their clinical, engineering, and computational foundations. The review also examines their integration with digital health architectures, edge computing systems, and tech driven personalized care. Methods: A structured literature search was conducted across PubMed, IEEE Xplore, Scopus, and Google Scholar for studies published between 2000 and 2025. Predefined search terms related to urinalysis, IoT, digital health, and microfluidics were applied. Sixty-five studies met the inclusion criteria. Data extraction focused on sensor technologies, digital health platforms, and reported case studies that demonstrated successful system deployment across diverse healthcare settings. Results: IoT-based urine screening technologies support real-time monitoring of biomarkers such as glucose, protein, and pH, which are essential for diagnosing conditions including diabetes, kidney disease, and urinary tract infections (UTIs). Emerging devices utilize optical, and acoustofluidic modalities, while BLE, Wi-Fi, and LPWAN serve as the primary connectivity standards. Discussion: IoT-driven digital transformation demonstrates strong potential to enhance the accessibility, efficiency, and diagnostic accuracy of urine screening. The convergence of biosensing, microfluidics and HDTs enables scalable, continuous, and personalized urine monitoring solutions. Despite these advancements, challenges related to data privacy, infrastructure readiness, and regulatory compliance remain significant barriers.