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Energy Footprint of Mechanized Agricultural Operations
Open AccessArticle

A Cloud-Based In-Field Fleet Coordination System for Multiple Operations

College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture, Beijing 100083, China
Institute for Bio-economy and Agri-technology (IBO), Centre for Research and Technology—Hellas (CERTH), 6th km Charilaou-Thermi Rd, GR 57001 Thermi, Thessaloniki, Greece
Authors to whom correspondence should be addressed.
Energies 2020, 13(4), 775;
Received: 16 November 2019 / Revised: 21 January 2020 / Accepted: 5 February 2020 / Published: 11 February 2020
(This article belongs to the Special Issue Supply Chain Management for Bioenergy and Bioresources)
In large-scale arable farming, multiple sequential operations involving multiple machines must be carried out simultaneously due to restrictions of short time windows. However, the coordination and planning of multiple sequential operations is a nontrivial task for farmers, since each operation may have its own set of operational features, e.g., operating width and turning radius. Taking the two sequential operations—hoeing cultivation and seeding—as an example, the seeder has double the width of the hoeing cultivator, and the seeder must remain idle while waiting for the hoeing cultivator to finish two rows before it can commence its seeding operation. A flow-shop working mode can coordinate multiple machines in multiple operations within a field when different operations have different implement widths. To this end, an auto-steering-based collaborative operating system for fleet management (FMCOS) was developed to realize an in-field flow-shop working mode, which is often adopted by the scaled agricultural machinery cooperatives. This paper proposes the structure and composition of the FMCOS, the method of operating strip segmenting, and a new algorithm for strip state updating between successive field operations under an optimal strategy for waiting time conditioning between sequential operations. A simulation model was developed to verify the state-updating algorithm. Then, the prototype system of FMCOS was combined with auto-steering systems on tractors, and the collaborative operating system for the server was integrated. Three field experiments of one operation, two operations, and three operations were carried out to verify the functionality and performance of FMCOS. The results of the experiment showed that the FMCOS could coordinate in-field fleet operations while improving both the job quality and the efficiency of fleet management by adopting the flow-shop working mode. View Full-Text
Keywords: agricultural machinery; fleet management; auto-steering system; collaborative operating system; flow-shop; simulation; field experiment agricultural machinery; fleet management; auto-steering system; collaborative operating system; flow-shop; simulation; field experiment
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MDPI and ACS Style

Wu, C.; Chen, Z.; Wang, D.; Song, B.; Liang, Y.; Yang, L.; Bochtis, D.D. A Cloud-Based In-Field Fleet Coordination System for Multiple Operations. Energies 2020, 13, 775.

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