Hough’s Transform-Based IoT Device for Automated Identification and Prediction of Blood Groups

Real-time data collection, sharing, and analysis of health-related information are made feasible using the Internet of Things (IoT) in the healthcare field. IoT could transform patient care, enhance clinical results, and optimize healthcare operations by integrating remote monitoring, automation, and data-driven decision-making. Determining the blood type is essential for safe blood transfusions, organ transplant compatibility, and preventing immunological responses. Additionally, the ABO blood group system prediction supports research on associations between blood types and various medical conditions, such as susceptibility to infections, cardiovascular diseases, and clotting disorders. Antigens (A and B) and the Rhesus (Rh) factor (+ or -) are usually used to determine blood grouping. By combining known antibodies with blood samples, the blood group can be examined by the agglutination reactions through image processing techniques. In this work, we proposed an intelligent portable blood analyser for blood type prediction and determination using an IoT-based system. The blood group identification and detection in blood samples is performed with a fabricated simulation device using a 3D Printer and acrylic materials. This system determines a solution using the adaptive Hough transform algorithm and provides the highest level of efficiency and accuracy in blood group identification and counting. Thus, the proposed system lowers the possibility of transfusion-related allergic responses and stores precise outcomes that exclude human-made errors, enabling us to instantly determine a person's blood type.