Framework for Automatic Blood Group Identification and Notification Alert System

Madeha Memon, Bobby Lalwani, Mahaveer Rathi, Yasra Memon, Knooz Fatima
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Abstract

Image Processing has assisted researchers in a variety of ways, especially in the areas of security and medicine fields. Identifying blood types in emergencies or far-off places and regions where experts have not been available is a present-day challenge. Therefore, we have developed an automatic system that will detect the blood group and notify an alert system using GSM and various image processing methods. Prior to any treatment or operation, it is necessary to determine the blood type for a transfusion of blood, even in an emergency. Currently, technicians manually conduct these tests, which can cause human mistakes. Different systems have been created to automate these tests; none have been successful in completing the analysis in time for emergencies. This project intends to create an automated system to do these tests quickly, adjusting to urgent circumstances. Initially, the slide test is performed to collect the blood images. Furthermore, various image processing methods have been performed for processing images using the PI camera. Subsequently, an alert with the patient's blood group is then generated and sent to the concerned patient or the hospital to immediately consult the patient. Unit testing and load testing were performed on 950 images at a time which yielded 97% accuracy.
血型自动识别和通知警报系统框架
图像处理为研究人员提供了多种帮助,尤其是在安全和医学领域。在没有专家的紧急情况下或遥远的地方和地区识别血型是当今的一项挑战。因此,我们开发了一种自动系统,利用 GSM 和各种图像处理方法检测血型并通知警报系统。在进行任何治疗或手术之前,都有必要确定输血者的血型,即使在紧急情况下也是如此。目前,技术人员手动进行这些测试,可能会造成人为错误。已有不同的系统实现了这些测试的自动化,但没有一个系统能在紧急情况下及时完成分析。本项目旨在创建一个自动化系统,以快速完成这些测试,并根据紧急情况进行调整。首先要进行玻片检测,收集血液图像。此外,还采用各种图像处理方法,使用 PI 相机处理图像。随后,系统会生成带有病人血型的警报,并发送给相关病人或医院,以便立即对病人进行会诊。一次对 950 幅图像进行了单元测试和负载测试,准确率达到 97%。
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