Optimizing Wireless Sensor Networks for Low-Latency and Secure Health Monitoring
DOI: https://doi.org/10.5281/zenodo.23208437
Abstract
Continuous health monitoring increasingly relies on wireless sensor networks (WSNs) capable of acquiring and transmitting physiological data in real time while maintaining low energy use, reliable communication, and acceptable delay. These systems are important for remote patient supervision, chronic disease management, elderly care, emergency monitoring, and smart healthcare. However, conventional architectures often treat energy efficiency, communication performance, intelligent analysis, and cybersecurity separately, creating trade-offs such as rapid battery depletion, packet loss, delayed alerts, inaccurate anomaly detection, and security vulnerabilities.
This study designs and evaluates an integrated hybrid health-monitoring framework combining energy-aware clustering, adaptive routing, machine-learning-based anomaly detection, data fusion, and lightweight authenticated encryption. A simulation-based comparative design was used with wearable and ambient sensors monitoring heart rate, body temperature, blood pressure, and oxygen saturation under varying node-density and traffic-load conditions. The proposed framework was compared with conventional LEACH and a security-enhanced LEACH variant.
In the 100-node scenario, the proposed framework achieved a network lifetime of 2,020 rounds versus 1,480 for LEACH, while reducing energy consumption from 72.4 J to 58.3 J. Packet delivery ratio increased from 91.8% to 98.1%, and latency decreased from 185 ms to 128 ms. Anomaly-detection accuracy reached 96.3%, while the security mechanism achieved an estimated 95% attack-resistance score. Performance remained stable under increased network density and traffic. Overall, the results demonstrate that integrated optimization of routing, analytics, energy, and security can improve WSN-based health monitoring, although validation using physical wearable devices, clinical datasets, and hospital-scale deployments remains necessary for practical implementation reliability.
How to Cite
TANNU, "Optimizing Wireless Sensor Networks for Low-Latency and Secure Health Monitoring", Vol. 4, Issue 6, 25-09-2026, pp. 30-43. DOI: https://doi.org/10.5281/zenodo.23208437
