Drone-Based Real-Time Air Pollution Monitoring System

In an effort to confirm the functionality of the sensors utilized in the IoT drone-based real-time air pollution monitoring system, preliminary experiments were conducted as part of the project's initial phase. Ensuring correct data collection can set up the requirements for reliable and precise measures. The installation of a Random Forest method was necessary to ensure continuous communication between hardware and software parts, which was necessary for the project's success. This technique effectively handles huge datasets and feature spaces with high dimensions, and it minimizes overfitting. It is used in air pollution monitoring systems to forecast air quality levels and categorize the severity of pollution. IoT drone-based real-time air quality monitoring system proved its capacity to provide accurate and useful data on air quality. Comprehensive testing was done under a variety of conditions to determine the system's effectiveness and robustness. The results of these experiments underscore the potential impact of this innovative system in safeguarding human health and the environment.