International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | To Implement and Analysis of Fingerprint-Based Blood Group Prediction and Emergency Donor Assistance System |
|---|---|
| ABSTRACT | The Intelligent Blood Group Prediction and Emergency Assistance System is designed to provide a non-invasive and efficient solution for blood group identification using Artificial Intelligence and biometric technologies. The system uses fingerprint analysis along with deep learning techniques, particularly Convolutional Neural Networks (CNN), to accurately predict blood groups with a confidence score. It eliminates the need for traditional blood testing methods, making the process faster and more accessible. The platform also integrates emergency assistance features such as donor matching and nearby blood bank suggestions for critical situations. By combining biometric analysis with real-time healthcare support, the system improves emergency response time and enhances overall medical efficiency. |
| AUTHOR | DEEPA G, LOGINI S, ASINTAJ H, MEERAKUMARI M Assistant Professor, Department of Computer Science and Engineering, P.S.V College of Engineering and Technology, Mittapalli, Krishnagiri, India. UG Scholar, Department of Computer Science and Engineering, P.S.V College of Engineering and Technology, Mittapalli, Krishnagiri, India. |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404054 |
| pdf/54_To Implement and Analysis of Fingerprint-Based Blood Group Prediction and Emergency Donor Assistance System.pdf | |
| KEYWORDS | |
| References | [1]. Qurat Ul Ain, Rimsha Sultan, Sara Mehveen, and Farhana, “Blood Group Detection Using Fingerprints and Image Processing,” Journal of Novel Research and Innovative Development (JNRID), vol. 3, no. 4, Apr. 2025. [2]. D. Siva and S. Sundhara, “Neural Networks for Fingerprint-Based Blood Group Prediction,” International Journal of Neural Systems, 2020. [3]. M. Elshafie, A. Mohammed, and H. Hassan, “Blood Group Identification via Fingerprint Patterns,” Journal of Biomedical Research, 2020. [4]. Pinki Kumari and Priyanka Singh, “Thumbprint Analysis for Blood Group Identification,” Indian Journal of Medical Sciences, 2021. [5] Akshay Dalvi, Rohit Patil, and S. Deshmukh, “Image Processing Techniques for Blood Typing,” Computer Vision and Applications Journal, 2021. [6]. R. Keerthana, S. Balaji, and M. Praveen, “Automated Blood Typing System Using Image Processing,” Clinical Diagnostics and Research Journal, 2021. [7]. Ricardo Fernandes, L. Costa, and P. Almeida, “Portable Device for Blood Group Detection Using Optical Density Variations,” Biomedical Engineering Advances, 2020. [8]. D. Jurafsky and J. H. Martin, Speech and Language Processing, Pearson, 2020. [9]. Vikas Shivhare, A. Tiwari, and N. Sharma, “Fingerprint-Based Disease and Blood Group Association Study,” Annals of Human Biology, 2019. |
