Abstract: Internet of Things development is of great significance for modern society progress. However, the limited information in some areas with incomplete infrastructure restricts Internet of Things development, so the long-distance information transmission task of sensor nodes needs to be put on the agenda. The research introduces beamforming technology for clustering wireless sensor nodes, and proposes a clustering algorithm based on wireless sensor node’s energy consumption rate for nodes energy management to achieve remote information sharing and transmission. The results confirm that the success rate of clustering algorithm based on beamforming event triggering increases with node density increasing, and the success rate is infinitely close to 1. In addition, when the sensor node is 120, the average charging delay time based on machine learning energy consumption prediction is only 946 seconds, which is reduced by 521 seconds compared to the Mean-shift algorithm. When sensor node is 120, the algorithm has a successful access count of up to 1288 times. These two clustering algorithms have good clustering performance and significant practical application effects, providing reliable technical support for remote data transmission in the modern Internet of Things.
