Automated Sleep Apnea Detection System with IOT-Enabled Alerts Using Multi-Sensor Fusion and ESP32 Microcontroller

Abstract

Sleep apnea is a serious and prevalent sleep disorder characterised by repeated episodes of partial or complete cessation of breathing during sleep, resulting in reduced oxygen supply to vital organs and disrupted rest patterns. Untreated sleep apnea leads to severe health complications including cardiovascular disease, hypertension, diabetes, and chronic fatigue. This paper presents the design and development of a low-cost, non-invasive, IoT-enabled automated system for real-time detection and monitoring of sleep apnea in a home environment. The proposed system integrates a respiratory sound sensor, a pulse sensor, an LM35 temperature sensor, and an SpO₂ sensor with an ESP32 microcontroller as the central processing unit. The ESP32 continuously acquires and processes multi-sensor physiological data including breathing patterns, heart rate, body temperature, and blood oxygen saturation. When abnormal conditions such as irregular breathing, low SpO₂, or abnormal heart rate are detected, the system activates a buzzer alert and simultaneously transmits real-time data to the Blynk IoT cloud platform for remote visualisation. Experimental results confirm that the system effectively monitors multiple physiological parameters and detects potential sleep apnea events with reliable performance, offering a portable and cost-effective alternative to conventional polysomnography.