Nano-Lungs: A Wearable Air Purification System Utilizing Graphene-Based Nano Filters and AI-Driven Air Quality Monitoring

This research proposes the design, fabrication, and comprehensive evaluation of Nano-Lungs, a novel wearable personal air purification system. The system integrates advanced graphene-based nanofilters with an AI-driven platform for real-time air quality monitoring and adaptive control. Its primary objective is to achieve mobile, high-efficiency removal of airborne particulate matter (PM1.0, PM2.5, PM10), volatile organic compounds (VOCs), and various biological contaminants. Concurrently, the device continuously monitors relevant environmental and physiological parameters to optimize its operation. The methodology synthesizes recent advancements in graphene nanomaterials, sophisticated filter fabrication techniques, micro-blower and power management hardware, and low-power environmental sensing. Edge AI techniques are employed for intelligent pollutant classification, anomaly detection, and the implementation of

adaptive control strategies. The study details the materials and methods for producing graphene oxide (GO) and reduced graphene oxide (rGO) filter media, outlines the integration of multi-layer filter architectures, and describes the electronic and firmware components for sensing and actuation. Experimental protocols for both laboratory and field testing are proposed. The work includes discussions on results derived from bench-top experiments, computational fluid dynamics (CFD) simulations, and prototype testing, alongside an examination of safety, biocompatibility, lifetime, and ethical considerations.

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