International Journal of Science, Engineering and TechnologyAuthors: Assistance Professor Y.V.Vamsi Krishna Teja, Bodduluri Deepika, kota Sri Tany, Bavanari Dhanya Sri, Rayudu Kavya Chowdary
Abstract: Anemia is a widespread health condition caused by a deficiency of hemoglobin or red blood cells, leading to fatigue, weakness, and other serious health complications. Early detection and continuous monitoring are crucial for effective treatment and prevention. Traditional diagnostic methods, such as invasive blood tests, are time-consuming, costly, and often inaccessible in rural or resource-limited areas. This study presents an IoT-based anemia detection system (HI-MASS) that utilizes temperature, heartbeat (BPM), and oxygen (SpO₂) sensors to monitor physiological parameters that correlate with anemia. The system collects real-time data through wearable devices, which are then transmitted to cloud servers and processed using predictive algorithms to detect anemia, classify its severity, and provide timely alerts. The integration of IoT technology with machine learning enables non-invasive, cost-effective, and real-time health monitoring, improving accessibility for remote populations. Experimental results demonstrate high reliability and strong potential for continuous anemia monitoring, making the proposed system a scalable and practical solution for proactive healthcare management.
