Author(s) :

Dr. Manjunath Gowda.

Volume/Issue :

Abstract :

Chronic respiratory diseases (CRDs) such as asthma and chronic obstructive pulmonary disease (COPD) pose substantial health challenges globally, requiring continuous monitoring for effective management. Traditional monitoring methods are often limited by episodic data collection and subjective assessments, which can delay intervention and worsen patient outcomes. Artificial intelligence (AI) offers transformative potential to overcome these limitations by integrating data from wearable sensors, environmental monitors, and electronic health records to enable real-time, personalized monitoring. AI algorithms can detect early signs of disease exacerbation, predict risk, and support tailored interventions, shifting care from reactive to proactive models. This article reviews current AI applications in CRD monitoring, explores the components of AI-enhanced systems, discusses clinical benefits, and addresses challenges such as data privacy, model bias, and integration barriers. We also highlight future innovations poised to advance precision respiratory medicine, improving patient quality of life while reducing healthcare costs. Through multidisciplinary collaboration and ethical implementation, AI-driven monitoring systems promise to revolutionize chronic respiratory disease management worldwide.

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