Development of a Compact IoT-Enabled Air Purification System for Indoor Air Quality Improvement

This study details the development of a compact, low-cost, IoT-enabled solar-powered air purification system targeted at the increasingly problematic urban air pollution issue in an environmentally friendly way. Research suggests that the majority of standard air purifiers intended for small and medium-sized rooms use up to 0.003 kWh (3 watts) an hour, while some advanced models differ depending on fan speed settings [1]. Urban air pollution has dire health implications, especially in dense cities where indoor air quality is vital. The system integrates three kinds of filters: HEPA, nylon, and polypropylene (surgical mask), which were evaluated for their efficiency in capturing particulate matter, especially PM2.5 and PM10. Based on the results, polypropylene fabric, commonly used with surgical masks, is revealed to be the most economically sensible as well as efficient filter material that has achieved an impressive degree of filtration efficiency at 87.50% using three layers whereas maximum recorded HEPA filters reached efficiencies of 78.29% over the same layer number. HEPA offers high filtration efficiency but happens to be costlier to make it less practical compared to low-budget applications. Nylon filters, as though cheap, showed lower efficiencies: two layers achieved a maximum of 56.25%. It operates with solar energy, which greatly reduces its dependency on the power grid and thus makes it an energy-sustainable device. The addition of IoT features enables real-time air quality monitoring and allows the system to dynamically adjust its operation to deliver optimal performance. Its modular design ensures ease of assembly, scalability, and suitability for diverse indoor environments. This innovative system exemplifies a highly successful integration of cost-efficiency, sustainability, and technology-and hence makes it an accessible and practical solution to improve air quality, particularly in resource-limited and energy-constrained settings.