Low-Cost, Low-Power IOT System for Real-Time Vital Signs Monitoring and Early Detection of Health Abnormalities in the Elderly, With Enhanced Privacy.
Andrew Agbor Atongnchong, The ICT University, Under the Mentorship of The University of BUEA-Faculty of Engineering & Technology;
Prof Tonye Emmanuel, The ICT University, Under the Mentorship of The University of BUEA-Faculty of Engineering & Technology;
Prof. Victor W. Mbarika, The ICT University, Under the Mentorship of The University of BUEA-Faculty of Engineering & Technology;
Email Address(es): atongnchong.andrew@ictuniversity.edu.cm, , tonye2018@hotmail.com, victor@mbarika.com
Abstract
With the rapid advancement of Internet of things (IoT) technologies, smart and connected healthcare systems have emerge as a promising solution for continuous and remote patient monitoring. This is particularly critical for elderly populations and patients with chronic conditions, where frequent hospital visits are costly and hectic. In this paper, we propose an experimentally validated Low-cost, low-power IoT-based remote health monitoring system designed for continuous acquisition of vital physiological parameters, including electrocardiogram (ECG), heart rate, blood Oxygen saturation (Sp ), and body temperature. The proposed architecture integrates wearable wireless sensors, energy-efficient clustering mechanisms, secure data transmission, and cloud-based storage and analytics. To address the limitations of existing systems, our methodology combines a hardware prototype with network-level simulations conducted using NS-3 and MATLAB to evaluate latency, energy consumption, packet delivery ratio, and scalability. Security and privacy of patient data are guaranteed through a lightweight encryption framework suitable for resource-constrained IoT devices, with comparative analysis against computationally expensive homomorphic encryption schemes. Experimental results demonstrates that the proposed systems achieve reduced latency, improved energy efficiency and reliable data confidentiality. The findings confirm the suitability of the architecture for real-time remote healthcare monitoring in smart city and rural healthcare environments.
Keywords: Internet of Things, Remote Healthcare Monitoring, Wireless Sensor Networks, security, Energy Efficiency, Wearable sensors.
