Next-Gen HVAC Technologies with K-Nearest Neighbors for Cloud-Optimized Allergen Filtration for Healthier Living Spaces

Improved allergen filtering and better living environments may be achieved with the help of new Heating, Ventilation, and Air Conditioning (HVAC) innovations introduced in this research, which use the K-Nearest Neighbours (KNN) algorithm. It provides a cloud-optimized method for allergen detection and filtering, acknowledging the vital role of HVAC systems in Indoor Air Quality (IAQ). Filtration settings are automatically adjusted in response to changing allergen levels by analyzing real-time environmental data using the KNN algorithm. In order to analyze data efficiently and make system modifications in a timely manner, the cloud optimization framework enables seamless connection between HVAC devices and a centralized server. Extensive testing in controlled settings allows us to prove that the suggested method greatly decreases airborne allergens. People with respiratory issues or allergies may benefit from the better indoor air quality the research suggests. The growing need for healthier living environments is being met by this study, which adds to the continuing efforts to develop smart and adaptable HVAC systems. To guarantee the ongoing improvement of IAQ and occupant well-being, KNN algorithm in conjunction with cloud optimization provides a scalable solution for practical applications.