Research on Innovative Decision-Making of IOT Landscape Engineering Based on Clustering Algorithm Network Control

With the continuous integration of Internet of Things (IoT) and clustering algorithm technology, its application in landscape engineering decision-making is gradually emerging. This study aims to explore the innovative application of IoT technology based on clustering algorithm network control in landscape engineering decision-making, with the aim of improving the intelligence, scientificity, and efficiency of the decision-making process. This paper first analyzes the characteristics and requirements of landscape engineering decision-making, and then elaborates on the basic principles of clustering algorithms and their advantages in the IoT environment. On this basis, this study constructed an IoT landscape engineering decision support system based on clustering algorithm network control. The system is capable of real-time collection and analysis of massive engineering data, and effectively integrating and classifying these data using clustering algorithms, thereby providing decision-makers with more accurate decision-making basis. In particular, we combined the [Formula: see text]-average clustering algorithm with IoT network control to conduct in-depth analysis and weight optimization of multiple decision factors in landscape engineering. Through a series of simulation experiments, we have verified the effectiveness and accuracy of the system in handling complex and multidimensional landscape engineering decision-making problems. The experimental results show that this method not only significantly improves the accuracy and efficiency of decision-making, but also opens up new avenues for intelligent management of landscape engineering.