IoT-Based Secure Remote Health Monitoring with Edge Signal-Quality Assessment and Intelligent Alert Logic

Abstract

IoT-Based Secure Remote Health Monitoring with Edge Signal-Quality Assessment and Intelligent Alert Logic 1Tania Khatun, 2Sayon Dey, 3Sudiksha Dasgupta, 4Dr. Tirthadip Sinha 1,2,3UG student, Dept. of Electronics and Communication Engineering, Haldia Institute of Technology, Haldia, Purba Medinipur, West Bengal 4Dept. of Electronics and Communication Engineering, Haldia Institute of Technology, Haldia, Purba Medinipur, West Bengal ABSTRACT Remote health monitoring often struggles with sensor noise and nuisance alarms. This paper presents a multi-layered IoT framework that evaluates data quality directly at the edge before triggering alerts or transmitting telemetry. Using an ESP32 paired with optical (MAX86141), temperature (MAX30205), and inertial (ICM-42670-P) sensors, the system evaluates channel-specific signal quality indices (SQI) to filter out motion artifacts. Rather than triggering on isolated threshold spikes, the alert engine requires persistent physiological abnormalities or verified motion sequences to flag events like falls. Structured observations—tagged with timestamps, quality states, and monotonic sequence numbers—are published securely over TLS-encrypted MQTT 5.0 to a monitoring dashboard. The architecture is validated using an eight-part engineering matrix demonstrating reliable data integrity, least-privilege security, and fault recovery.