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Model and System for Cotton-picker Operation Scheduling
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: 2015 ASABE Annual International Meeting 152190305.(doi:10.13031/aim.20152190305)Authors: Caicong Wu, Jing Zhao, Jie Wang, Lin Zhou, Yaping Cai
Keywords: Cotton-picker, Operation Scheduling, System, Model
Abstract. Xinjiang province lies in the northwest of China and is an important region of cotton cultivation. Usually the area of the farms is more than 20,000 ha. Several cotton-picker harvesting service companies have more than 100 cotton-pickers. There are two kinds of cotton-picker, i.e., 6-row John Deere, 5-row CASE. Sometime they will use the Guihang Cotton-picker made in China. In this paper, a Cotton-picker Operation Scheduling System (CPOSS) was developed for dispatching machines and labors, and guide the labors to the target field. CPOSS is a WebGIS based management software. The whole scheduling process mainly includes three modules. The overall scheduling module aims to help the general manager to create fleet groups according to total operation demands of customers and the supply capacity of its own company. He will comprehensively select different types and age of cotton-picker to ensure efficiency and fairness. A real-time evaluation model is studied to adjust the rationality in real-time. The local scheduling module is to dispatch the machines and labors to the fleet. Different cotton-picker needs different numbers of labors, CASE cotton-picker need one additional security person. The center navigating module cotton-picker is to guide the staff to the specific field in the farm every day. The Google Maps based APP software is developed for center navigating, which receives the guidance commands from the CPOSS by SMS (GSM short message) and initiates the app to create the optimal path for the driver with the handhold mobile phone. Experiment was arranged during the autumn of 2014. Five cell phones were used for the harvesting monitoring and dispatching experiment. Preliminary application shows that the model and system can improve the management efficiency of cotton picking operation.
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