Date of Publication :7th January 2026

Abstract: Rapid and reliable blood analysis is critical in emergency and point-of-care healthcare, yet conventional laboratory-based blood group detection and cell counting methods are time-consuming, reagent-dependent, and require skilled personnel. This paper presents an IoT-enabled microfluidic diagnostic system that integrates blood group identification, complete blood cell (CBC) counting, and alcohol detection within a single portable embedded platform. The proposed system employs a microfluidic lab-on-chip structure combined with impedance-based sensing and optical detection to analyze a finger-prick blood sample. An Arduino-based embedded processor performs real-time signal processing and displays results instantly on an LCD, while enabling digital data logging. The integrated alcohol detection module provides additional emergency screening capability. The Proposed system reduces sample volume, minimizes manual intervention, and enables rapid point-of-care diagnostics compared to traditional screening. Performance evaluation demonstrates reliable detection accuracy with low latency, making the proposed system suitable for emergency rooms, ambulances, and resource-limited healthcare environments. This model in future possibilities to include machine-learning-assisted cell classification and cloud-based data analytics.

Reference :