aspg-18-2862-1792025600 20261015005320 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Intelligent Systems and Internet of Things JISIoT 2769-786X 2690-6791 2024 13 1 Shagun Agarwal Professor, School of Allied Health Sciences, Galgotias University. Greater Noida, India Lekha Bist Professor cum Dean, Galgotias School of Nursing, Galgotias University, Greater Noida, India Suresh Kumar Sharma Clinical & Nursing Informatics Specialist, CDAC, Pune Sunil Kumar Dular Professor cum Dean, Faculty of Nursing, SGT University, Gurugram- 122505- India Rupali Salvi Professor, Bharati Vidyapeeth College of Nursing, Pune, Maharashtra, India This research introduces a novel approach to intelligent IoT-based audio signal processing for healthcare applications. Leveraging advanced feature extraction techniques such as Mel-Frequency Cepstral Coefficients (MFCC) and Wavelet Transform, combined with sophisticated classification models like Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs), the proposed method demonstrates superior performance in accurately classifying healthcare data. Through extensive experimentation and analysis, the method achieves high accuracy, precision, recall, and F1 score, while exhibiting robustness in discriminating between different classes and maintaining precision in classification, as evidenced by its high AUC-ROC and AUC-PR values. The ablation study provides insights into the significance of key components and parameters, offering guidance for further refinement and optimization of the method. Overall, the proposed method holds promise for revolutionizing healthcare management through proactive monitoring and intervention, leading to improved patient outcomes and healthcare delivery. 2024 83 98 2862 https://creativecommons.org/licenses/by/4.0/ 10.54216/JISIoT.130107 https://americaspg.com/journal/18/article/2862 https://americaspg.com/storage/61717403774.pdf