Merazga, Ammar
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Design of a secure-cloud remote medical monitoring system using the P-QRS-T electrocardiogram detection algorithm Khalef, Rostom; Moulahcene, Fateh; Merazga, Ammar
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10730

Abstract

The COVID-19 pandemic has highlighted the limitations of traditional healthcare, resulting in higher mortality rates among children, the elderly, and healthcare workers. This situation has created a pressing need for urgent medical care from healthcare professionals. This paper presents a secure cloud-based remote medical monitoring system that integrates the internet of things (RMMS-IoT) with advanced P-QRS-T electrocardiogram (ECG) detection algorithms to enable real-time, accurate vital sign analysis. The system combines microcontroller devices, wearable sensors, and medical-grade equipment, leveraging hypertext transfer protocol secure (HTTPS) and Blynk bridge cloud technologies to ensure data security and interoperability. The RMMS-IoT system demonstrated high accuracy in monitoring vital signs by comparing its results with data from actual measuring devices, showing errors in body temperature readings below 1% and heart rate (HR) measurements below 2.8%. The algorithm used to detect P-QRS-T features from the ECG exhibited robust performance in differentiating between normal and abnormal ECG patterns in patients, and it achieved an accuracy rate of 90% in ECG classification.
IoT-enabled connected incubator with redundant communication for real-time neonatal monitoring Mellal, Naçima; Maatallah, Soumia Hadj; Merazga, Ammar; Bouchouareb, Rachida; Nacer, Souad
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 2: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i2.pp633-644

Abstract

Premature birth remains a major challenge in neonatal care, especially in resource-constrained settings, where continuous monitoring and timely intervention are limited. Most existing neonatal incubators offer limited real-time monitoring, unreliable alerting, and lack communication redundancy, potentially delaying critical responses. This paper presents a comprehensive internet of thing (IoT) enabled connected incubator with redundant communication (Wi-Fi and GSM) for real-time monitoring of physiological and environmental parameters. The system integrates sensing, processing, cloud connectivity, a mobile application, and multi-channel alerts (App notifications, SMS, voice calls, and local alarms). It was experimentally evaluated under controlled laboratory conditions. Quantitative evaluation shows a cloud transmission success rate of 99.1%, end-to-end communication latency below 1 second via Wi-Fi and 2.2 seconds via GSM, with 98% of alerts successfully delivered within 6 seconds. The proposed system provides a low-cost, reliable platform that enhances neonatal safety, supports timely clinical decisions, and is scalable for resource-constrained healthcare environments.