Abstract

Volatile Organic Compounds (VOCs) in human breath contain important biochemical data that can be used as early warning signs for health risk awareness systems. The proposed research work brings forth an AI pattern that utilizes VOC patterns to ensure health screening is noninvasive, rapid, and inexpensive. The proposed system combines health data acquisition through sensor technology and sophisticated machine learning algorithms to detect minute changes in VOC patterns and convert them into predictive risk profiles. A prototype system has been developed to test real-time breath monitoring through IoT technology and a mobile feasibility interface, proving the feasibility of portable health screening outcomes. Experimental methodologies have been used to ensure the system is highly sensitive and specific in detecting minute health anomalies while remaining cost-effective. This study brings together the ideas of artificial intelligence and breath analysis to help in the development of proactive and preventive healthcare technology that is less invasive in terms of health screening. The proposed system fills the gap that exists between the laboratory-based diagnostic systems and the health resources available in the community that are more accessible. The system that involves sensor integration and AI recognition is one of the approaches through which portable technology and the power of breath are able to provide valuable chemistry. The prototype system indicates the significance of affordability and flexibility in ensuring that the system is relevant in the context of healthcare monitoring. The smartphone interface enhances the usability of the system and encourages proactive personal health.