Intelligent Non-Invasive Breath Acetone Monitoring System Using ESP32, MQ-138 Sensor, and Machine Learning Algorithms
收藏IEEE2026-04-17 收录
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https://ieee-dataport.org/documents/intelligent-non-invasive-breath-acetone-monitoring-system-using-esp32-mq-138-sensor-and
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资源简介：
A non-invasive system for detecting acetone in breath using ESP 32 with MQ-138, integrated with machine learning algorithms for classification. The system detects acetone levels in exhaled air that 1.76 for monitoring diabetic. His script presents a hybrid system for diabetes prediction, it combines SVM for non-linear pattern detection, Random Forest for robustness and feature importance, and a Neural Network to integrate both outputs via backpropagation. The model ensures high accuracy for healthcare use.
提供机构：
Jose Luis Robles Barcenas; Moisés Vicente Márquez Olivera; Viridiana G. Henández Herrera
