(untitled) (International Journal of Latest Technology in Engineering Management & Applied Science, 2025)
Abstract: Over 1.6 billion people worldwide suffer from anaemia, which is still a major public health concern. Low-resource environments bear a disproportionately high burden of this condition. Although conventional blood tests necessitate invasive procedures, trained personnel, and laboratory infrastructure, early detection is essential to preventing serious clinical outcomes. Using a Raspberry Pi platform and Internet of Things (IoT)-enabled remote monitoring, this work introduces AcuSense, a portable, non-invasive anaemia detection system that combines photoplethysmography (PPG) and conjunctiva image analysis. The system uses deep learning-based conjunctiva imaging and real-time PPG signal acquisition to provide highly accurate haemoglobin level estimates. IoT integration improves accessibility for underserved and rural communities by enabling automated data storage, cloud analytics, and remote healthcare provider alerts. Strong correlation between experimental evaluation and conventional haemoglobin measurement techniques highlights AcuSense's potential as an affordable, quick, and non-invasive diagnostic tool.