Embedding Environmental Intelligence in Low-cost Drones

Effective environmental monitoring is key in our rapidly changing world, where environmental metrics such as temperature, humidity, and air quality can unexpectedly fluctuate and cause health risks and ecological imbalances and alter informed policymaking. Traditional monitoring paradigms, often associated with latency and high costs, are becoming progressively inadequate for real-time data analysis and decision-making demands. Addressing this critical gap, this paper unveils a cost-effective option for leveraging Aerial Vehicles. The Tello EDU drone, integrated with highly accurate sensors and interfaced with a Raspberry Pi 4B for advanced data processing, brings to life a potential replacement for current environmental monitoring systems. The paper delineates a comprehensive system architecture that synergizes airborne sensing with ground-level data synthesis, enabling instantaneous environmental analytics. Our approach focuses on a new era of community-centric and governance-responsive environmental surveillance. Preliminary results are promising, showcasing the proposed system's capability to transcend the limitations of existing methodologies by delivering a more efficient and scalable solution for environmental oversight.