3results about How to "Improve load utilization" patented technology

The invention discloses a garbage truck real-time monitoring and remote scheduling method based on the Internet of Things, and the method comprises the following steps: S1, collecting the real-time data of the operation state of a garbage truck, and carrying out the preprocessing of the real-time data; s2, constructing a task prediction model based on an improved adaptive graph neural network, and generating a preliminary task distribution matrix and a path planning scheme; s3, optimizing the preliminary task allocation matrix and the path planning scheme by adopting an improved PPO algorithm; s4, the optimized task allocation matrix and the path planning scheme are sent to a garbage truck vehicle-mounted terminal, and the task completion rate and the path deviation value are calculated; s5, the operation state of the garbage truck is monitored in real time, and the monitoring result and the operation state data are transmitted to the cloud Internet of Things platform; and S6, dynamically updating the scheduling instruction. According to the method, the Internet of Things, the adaptive graph neural network and the improved PPO algorithm are fused, intelligent scheduling and real-time optimization of the garbage truck are realized, and the method has the advantages of high efficiency, stability and low-cost operation.

This application discloses a load balancing method and related equipment for distributed storage links, which can effectively improve the overall load utilization of a distributed storage system. The method includes: obtaining initial link grouping information corresponding to the distributed storage, wherein the distributed storage includes M storage links; determining T data acquisition time points corresponding to the current processing cycle; acquiring load data corresponding to each of the M storage links based on the T data acquisition time points; determining a first maximum load value corresponding to the M storage links based on the initial link grouping information and the load data; determining a second maximum load value corresponding to target link grouping information based on the load data and the initial link grouping information; and adjusting the M storage links according to the target link grouping information if the difference between the second maximum load value and the first maximum load value satisfies an adjustment condition.