## 6 Conclusions  
Regarding research on UAV path planning for carbon dioxide emission monitoring of land-side heavy vehicles in ports, the contributions made in this paper are as follows:  
1. It proposes a method for monitoring the land-side carbon dioxide emissions of the port to provide a more accurate carbon dioxide emission inventory (CEI) for the port. Additionally, a UAV monitoring path planning scheme for carbon dioxide emission monitoring on the port land side is presented. A rational mathematical model is constructed to consider the impact of safety and path length on the total cost, offering a novel perspective and research framework for subsequent carbon dioxide emission data monitoring tasks in the port area.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**Simulation Experiment Three**} \\ \hline \multirow{2}{*}{**Algorithm**} & **Minimum Path** & **Average Turning** & **Average Collision** \\  & **Length** & **Count** & **Count** \\ \hline A* & 62.53 & 9 & 9 \\ \hline IEA & 66.63 & 20 & 1 \\ \hline IEHA & 62.52 & 5 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Performance comparison of path planning algorithms.  
Figure 14: Comparison of planning paths by algorithms.  
2. A systematic analysis of the path planning scheme for carbon dioxide emission monitoring on the land side of ports, focusing on heavy vehicles, was conducted to identify the causal and effect factors influencing the monitoring program. A hierarchical diagram of the influencing factors was established. This analysis aids subsequent researchers in recognizing and understanding the key issues and challenges that may arise during the implementation of the monitoring program, offering guidance for further in-depth studies.
3. Focusing on the initial path planning in the UAV monitoring process, an improved algorithm (IEHA) is proposed and verified through simulation experiments. The new algorithm ensures a safer and more reliable path generation. It optimizes path length and smooths the path, avoiding the risks associated with sharp turns, offering a new insights into solving the UAV monitoring path planning problem.  
This paper addresses the issue of monitoring heavy truck carbon dioxide emissions on the land side of the port using UAVs to improve the port's carbon dioxide emission inventory and contribute to the realization of energy-saving and green ecological goals. The focus of our study is on the initial UAV path planning problem, with potential for in-depth research on subsequent stages such as UAV task reallocation, path replanning, and coordination of multi-UAV monitoring tasks. Additionally, the path simulation experiments conducted are in a two-dimensional environment, with future experiments potentially incorporating three-dimensional real-world scenarios. Future research should delve into the limitations of UAV monitoring technology and explore ways to boost energy efficiency, optimize communication protocols, enhance environmental adaptability, and conduct in-depth studies on regulations and safety standards to ensure the legality and safety of UAV operations. These issues will become the key directions for our future research.  
X.W.: Conceptualization, Methodology, Writing--original draft, Investigation, Software, Data curation. Z.L.: Writing--review, Investigation, Validation. X.C.: Conceptualization, Methodology, Supervision. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Key Research and Development Program of Hubei Province, China (Grant ID: 2023 BAB097).  
Not applicable.  
The data supporting this study are not publicly available due to privacy.  
Requests for access to these data should be directed to [PERSON], [EMAIL_ADDRESS].  
We would like to thank [PERSON] for his insightful comments on the manuscript.  
The authors declare no conflicts of interest.