IoT-Enabled UAV for Real-time Atmospheric Analysis and Predictive Weather Modelling

The integration of Artificial Intelligence of Things (IoT) with Unmanned Aerial Vehicles (UAVs) presents unprecedented opportunities for real-time environmental monitoring and predictive analytics. This paper presents the design and development of a quadcopter drone system embedded with IoT-enabled environmental sensors for real-time atmospheric data collection and wireless cloud transmission. The system incorporates a brushless motor quadcopter frame, electronic speed controllers (ESCs), a flight controller for stabilization, and a suite of atmospheric sensors including temperature, humidity, pressure, and air quality modules interfaced with a microcontroller. Collected data is transmitted to a cloud platform via Wi-Fi or LoRa wireless communication for live monitoring and analysis. Additionally, a machine learning-based rain prediction module is proposed as a future enhancement, enabling the UAV to forecast rainfall patterns based on atmospheric readings. The system is evaluated for flight stability, data accuracy, transmission latency, and sensor reliability across multiple test flights. Experimental results demonstrate the viability of the proposed system for smart agriculture, disaster monitoring, and environmental surveillance applications, with a cost-effective and scalable architecture adaptable for advanced IoT deployments.