IoT-Based Sleep Quality Monitoring Simulation With Sleep Condition Analysis Using Fuzzy Logic - M LUTFI MA (IndoCompt Publisher, 2026)
This research aims to develop a low-cost IoT-based sleep quality Monitoring Simulation with Sleep Condition analysis using fuzzy logic for real-time physiological data acquisition and classification. The study employed the ADDIE development model (Analysis, Design, Development, Implementation, Evaluation). The system integrates MAX30100 heart rate sensor, DHT22 temperature sensor, and MPU6050 motion sensor with an ESP32 microcontroller. A Mamdani fuzzy inference system was implemented to classify Sleep Conditions based on heart rate, body temperature, and body movement parameters. The system was simulated using Wokwi and Cisco Packet Tracer, with fuzzy rules developed in MATLAB and embedded programming in Arduino IDE. The Blynk IoT platform was utilized for remote monitoring. Validation included Black Box Testing and User Acceptance Testing (UAT) with ten respondents. The system successfully acquired real-time physiological data and transmitted it to the Blynk cloud platform. The fuzzy logic algorithm effectively processed sensor data uncertainty, classifying health conditions into