Daily Archives: May 13, 2025

Enhancing Healthcare Accessibility, Risk Prediction, and Digital Record Management – Maternal and Child Health Monitoring System
Authors:-Shapna Rani E, Associate Nandhini S, Shwetha B, Sree Suvetha G, Thanzia Z

Abstract-:The Maternal and Child Health Monitoring System is an AI-driven solution designed to improve maternal and newborn healthcare by tracking essential health data, predicting risks, and streamlining administrative processes. Its mission is to “Empower mothers and ensure child well-being through personalized health tracking and AI-powered risk assessments.” The digital health monitoring application is designed to improve maternal and child health outcomes by tracking essential health data, predicting risks, and streamlining administrative processes. For pregnant women, the allows users to input health metrics such as blood pressure, weight, and glucose levels, using machine learning to predict potential health risks like gestational diabetes and preeclampsia. Post-birth, the records essential child details (e.g., birth time, date, gender) and assigns a unique ID to track developmental milestones, vaccinations, and growth metrics. This ID also facilitates the issuance of digital birth certificates, integrating seamlessly with government systems for legal registration. The sends reminders for checkups and vaccinations to ensure timely healthcare for both mothers and children. Data is securely stored in a database, providing authorized users such as parents and healthcare providers with accessible, real-time information. The system also offers recommendations for personalized health, guidance, and mental health support. By combining health monitoring, predictive analytics, and administrative automation, the application offers a comprehensive solution that improves maternal and child health, simplifies birth registration, and ensures efficient healthcare management. Key Features include AI-powered risk prediction, real-time health tracking, Unique ID-based record management, vaccination reminders, digital birth certification, and multi-language support for broader accessibility.

DOI: 10.61137/ijsret.vol.11.issue2.459

Published by: Kajal Tripathi

Integrated Approaches to Computer System Validation Within GxP-Compliant Pharmaceutical Quality Management Systems
Authors:-Aditi Akundi, Dr. Pavithra G, Dr. Swapnil SN

Abstract-:The pharmaceutical industry is heavily regulated due to the direct impact of its products on human health and safety. To ensure compliance and maintain data integrity, regulatory authorities such as the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), and others require that computerized systems used in Good Practice (GxP) environments undergo rigorous validation. Computer System Validation (CSV) plays a pivotal role in ensuring that such systems consistently perform according to their intended use and comply with applicable regulations. This paper provides an in-depth conceptual overview of CSV within the framework of pharmaceutical Quality Management Systems (QMS). It explores its regulatory basis, the validation lifecycle, risk-based approaches, common challenges, and industry best practices, while highlighting the significance of CSV in maintaining quality, compliance, and patient safety.

DOI: 10.61137/ijsret.vol.11.issue2.458

Published by: Kajal Tripathi

Artificial Intelligence in Energy Management: A Comprehensive Literature Review on Methods, Applications, and Challenges
Authors:-Jayendra Jadhav, Aashirwad Mehare, Aditya Wandhekar, Sanyukta Pawar, Pranjal Chavan, Vedant Nigade

Abstract-:The mounting pressure for efficient and sustainable energy solutions has driven the adoption of Artificial Intelligence (AI) in contemporary energy systems. This literature review consolidates evidence from more than 20 recent studies on AI-based approaches for renewable energy and smart grid management. It discusses AI methods like machine learning, deep learning, reinforcement learning, and optimization techniques applied in energy forecasting, load management, fault detection, and demand response. The review emphasizes AI’s application in improving energy efficiency, lowering costs, and facilitating decentralized energy systems. It also touches on the most important hardware devices involved, e.g., photovoltaic panels, smart meters, IoT devices, and battery storage systems. Although it has the potential to transform, the use of AI in energy systems is confronted with various challenges such as high infrastructure expenditure, data needs, system integration problems, and regulatory issues. This paper concludes by establishing research gaps and outlining future directions for the complete utilization of AI to achieve a sustainable and intelligent energy ecosystem.

DOI: 10.61137/ijsret.vol.11.issue2.457

Published by: Kajal Tripathi