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Stream/Area:
-
Subject:
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Paper ID:
10.55041/IJSREM.RACCES027
Volume:
10 |
4 |
April 2026
Pages:
1--
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Breast milk is the most essential source of nutrition for newborn infants, especially for premature and medically fragile babies. However, several mothers face challenges in providing sufficient breast milk due to medical conditions or low lactation. Human milk banks help address this issue by collecting, storing, and distributing donated breast milk to infants in need. Traditional milk bank management systems rely on manual processes and isolated data storage, which can lead to inefficiencies in donor management, milk inventory tracking, and distribution coordination. This paper proposes a Cloud Enabled Smart Breast Milk Management System that utilizes cloud computing technologies to improve the management and accessibility of donor breast milk. The system provides a centralized platform for donor registration, milk collection tracking, inventory monitoring, and distribution management. Cloud infrastructure ensures scalability, reliability, and secure data storage while enabling real-time data access for healthcare providers. To enhance system performance, algorithms such as Load Balancing and Round Robin Scheduling are integrated to efficiently manage cloud resources and handle multiple user requests. Additionally, a machine learning-based donor recommendation system using the K-Nearest Neighbors (KNN) algorithm is implemented to identify suitable donors based on parameters such as health condition, blood group compatibility, location, and milk availability. The proposed system improves operational efficiency, reduces manual errors, and ensures timely availability of safe breast milk for infants. This technology-driven solution contributes to improved neonatal healthcare outcomes and better management of human milk banks.
KEYWORDS
The Cloud Enabled Smart Breast Milk Management System provides an efficient and reliable solution for managing the operations of human milk banks. Breast milk is a critical source of nutrition for newborn infants, especially premature and medically fragile babies who cannot receive sufficient milk from their mothers. The proposed system uses cloud computing technologies to create a centralized platform for managing donor information, milk collection records, storage monitoring, and inventory management. By integrating cloud infrastructure, the system enables real-time data access and secure storage of important information. Hospitals, donors, and milk bank administrators can easily access the system from different locations, improving coordination and communication between healthcare centers. The inclusion of intelligent algorithms such as load balancing and round robin scheduling helps the system efficiently handle multiple user requests and maintain high system performance. Additionally, the donor recommendation module plays an important role in identifying suitable donors based on parameters such as health condition, blood group compatibility, location, and milk availability. This helps healthcare providers quickly find appropriate donor milk for infants in need. Overall, the proposed system reduces manual effort, improves data accuracy, and enhances the efficiency of milk bank management, ultimately contributing to better neonatal healthcare outcomes.
1. Cesar G. Victora, et al., “Breastfeeding in the 21st Century: Epidemiology, Mechanisms, and Lifelong Effect,” The Lancet, vol. 387, no. 10017, pp. 475–490, 2016. 2. Norbert Haiden and Andreas Unterasinger, “Human Milk Banking: What We Know and What We Do Not Know,” Journal of Pediatric Gastroenterology and Nutrition, 2018. 3. PATH, “Strengthening Human Milk Banking: A Global Implementation Framework,” PATH Human Milk Banking Initiative, 2019. 4. Andrew C. Lee and Gary L. Darmstadt, “Impact of Donor Human Milk on Neonatal Health Outcomes,” Pediatrics Journal, 2020.
Publication Date
5/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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