A DEEP-LEARNING AND IOT-BASED AUTOMATED CLASSIFICATION OF LUNG DISEASES

Abstract

In 2020, respiratory diseases caused over 86 thousand deaths in Pakistan, ranking the country 8th in the world for this health hazard. The majority of the population does have access to adequate healthcare facilities, including the 61.8% of Pakistanis who live in luial aieas. The combination of a lack of infrastructure, health literacy severely limits the healthcare options for necessitates the development of intelligent systems that are able to restructure responsive and timely healthcare approaches for rural alleviation of respiratory diseases. not trained personnel, and most citizens. This situation communities, aiding in the To develop improved healthcare facilities, piopose the integration of deep learning we and the Intel net for advanced remote caregiving solutions. Oui proposed solution achieved exceptional performance with 95.05% the Asthma Detection Dataset Version 2[10], comprising 1,211 lung sound samples across 5 respiratory conditions. The system is based around three components: The IoT smart stethoscope, the deep learning-model-based data classification achieving clinical-grade performance, and the analysis and visualization web application. accuracy on With the inclusion of these components, the goal of our system is to transform respiratory healthcare in Pakistan, transformation especially for the rural population, lequires the responsible development of sophisticated devices while concurrently enhancing individual health seek to This diagnostic management capabilities. We mitigate the accessibility and knowledge gap between patients and health practitioners using modern technologies combined with simple-to-use applications.