Maritime Emission Monitoring: Development and Testing of a UAV-Based Real-Time Wind Sensing Mission Planner Module

Abstract

Maritime emissions contribute significantly to global pollution, necessitating accurate and efficient monitoring methods. Traditional methods for tracking ship emissions often face limitations in real-time data accuracy, with wind measurement being a critical yet challenging aspect. This paper introduces an innovative mission planner module for unmanned aerial vehicles (UAVs) that leverages onboard wind sensing capabilities to enhance maritime emission monitoring. The module’s primary objective is to assist operators in making informed decisions by providing real-time wind data overlays, thus optimizing flight paths and data collection efficiency. Our experimental setup involves the testing of the module in simulated maritime environments, demonstrating its efficacy in varying wind conditions. The real-time wind data overlays provided by the module enable UAV operators to adjust their flight paths dynamically, reducing unnecessary power expenditure and mitigating the risks associated with low-battery scenarios, especially in challenging maritime conditions. This paper presents the implementation of real-time wind data overlays on an open-source state-of-the-art mission planner as a C# plugin that is seamlessly integrated into the user interface. The factors that affect performance, in terms of communication overheads and real-time operation, are identified and discussed. The operation of the module is evaluated in terms of functional integration and real-time visual representation of wind measurements, and the enhanced situational awareness that it can offer to mission controllers is demonstrated. Beyond presenting a novel application of UAV technology in environmental monitoring, we also provide an extensive discussion of how this work will be extended in the context of complete aerial environmental inspection missions and the future directions in research within the field that can potentially lead to the modernization of maritime emission monitoring practices.

Comparative Analysis of Meteorological versus In Situ Variables in Ship Thermal Simulations

“…On the other hand, in atmospheric pressure and wind direction there is hardly any difference. Other authors also found wind measurement being a critical challenging aspect [ 25 ].…”

Tuning the Proportional–Integral–Derivative Control Parameters of Unmanned Aerial Vehicles Using Artificial Neural Networks for Point-to-Point Trajectory Approach

“…In this study, Mission Planner is used as the flight planning and simulation program. Furthermore, the quadrotor dynamics [19] required for flight are provided by embedded libraries in the Mission Planner open source software [20].…”

Swarm of Drones in a Simulation Environment—Efficiency and Adaptation

“…An exploration of evolutionary algorithms in enhancing the design and problem-solving capabilities of swarm robotics is presented in [17]. The article in [18] demonstrates the innovative applications of swarm robotics in theoretical and practical domains. Distributed collaborative partial SLAM for efficient navigation of autonomous robots [19] and the development of control algorithms for group formation flights in dense environments [20] can improve coordination within drone swarms.…”