Field Readiness and Operation Scheduling

Abstract

Knowing the readiness of a field for an agricultural operation is an important factor when creating seasonal and daily operational plans. To insure an efficient use of resources farm managers and agricultural contractors must make difficult decisions and must often rely on a "gut feeling". A large amount of information may be available, such as meteorically and geographical data, however this must be filtered and converted in to actionable knowledge in order for it to be useful. In this paper, a participatory approach is used to develop a concept of a Decision Support System (DSS) to make recommendations as to when a field is ready for an agricultural operation. Soft Systems Methodology (SSM) is used to clarify the current situation, which is inherently difficult to model due to the organic nature of the system and subjective opinions of those involved. The result of the SSM is a model that is the direct outcome of the experience of farm managers and agricultural contractors, and that can further be understood by computer scientists. The system of the proposed DSS is described in terms of the feasible datasets required and the inter relationships between the datasets, as well as suggestions of the level of detail of data. The proposed DSS is aimed to either operate as a stand-alone system taking direct inputs, or under a larger Farm Management Information System (FMIS) framework.

Infield optimized route planning in harvesting operations for risk of soil compaction reduction

“…Considering the constrained time frames operators are forced to work on due to weather conditions or farm scheduling limitations, it obliges them to drive under suboptimal soil conditions increasing soil compaction issues (Edwards, 2015;Edwards et al, 2016;Orfanou et al, 2013).…”

Service Scheduling Using an Agent Based Model with GIS Integration

“…Here, authors used operation start and processing times to calculate actual completion time at a farm. In another example, problem of scheduling multiple machines taking into account the field readiness has been tackled (Edwards 2015). Second type of path planning is in-field path planning problem; the ways in which given field can be traversed so that the operation can be completed in minimum time [ (Ryerson and Zhang 2007), (Hameed, Bochtis and Sorensen 2013), (Oksanen 2007)].…”