Addressing Uncertainty in Temporal and Spatial Scheduling for Farm Machinery Operation

Uncertainty is an important characteristic of scheduling model for scale farm machinery operation organizing. Practice shows that scheduling model without considering uncertainties is nearly useless. Uncertain influence factors arisen from natural environment, society and economy, market and supply, and customer and behavior, exist widely, emerge frequently, and affect production deeply. Uncertainties interfere with the allocation of productive factors on temporal and spatial dimensions for farm machinery operation scheduling and management. Questionnaire for farm machinery organizations was designed and finished in 2014. Both occurrence frequency and influence degree for each factor were quantified. Four influence factors including operation location change, weather mutation, parts supply delay, and operation skill defects appear in both list of high occurrence and deep influence. Then results of questionnaire and results of specific investigation were used to study temporal and spatial scheduling model and system for farm machinery management. Three case studies are introduced. The first case is about the uncertainty and countermeasure of forage harvesters scheduling and monitoring for a professional forage plantation company. The second case is about the uncertainty and counter measure of cotton-picker scheduling and monitoring for a professional cotton picking company. And the third case is about the uncertainty and countermeasure of social service management for a professional cooperative. The cases show that the research has strong pertinence to deal with uncertainties and can improve management efficiency of farm machinery operation.

Auto-steering based precise coordination method for in-field multi-operation of farm machinery

Multi-operation within a field and multi-machinery within a machinery operation are common in the scene of scaled farm machinery service,especially with soaring usage of automated steering system in small and medium machinery cooperatives.The object of this study was to explore a precise and efficient in-field coordination method to realize flow-shop scheduling for farm machinery fleet equipped with RTK-GNSS based auto-steering system.The new method is based on three-dimensional coordinate system(XYZ),within which the concept of field,operation strip,and operation task were defined.Under this concept framework,the operation strip state was further defined and its updating algorithm was designed,which can be used for optimization simulations and experiments.To evaluate the method,the waiting time between simulation and a real-world case was compared,and one cloud based prototype system was developed to demonstrate the practicability in the field by using NX200+automated steering system.The simulations showed that the in-field coordination can shorten the waiting time between two adjacent operations.The waiting time between rotary hoeing and seeding can be shortened from 4 h to 6.3 min.The field experiment showed that the prototype system could keep good consistency of ridges for a fleet by sharing the guidance line.

Research on Virtual Simulation of Seeder

In this study, the modeling and simulating of seeder were researched, and the method of virtual designing of seeder using computer was implemented. Based on these, general method of seeder virtual simulation was implemented using eon studio. The virtual designing, operation showing of farm machinery can be operated on website.

Automation and digitization of agriculture using artificial intelligence and internet of things

The growing population and effect of climate change have put a huge responsibility on the agriculture sector to increase food-grain production and productivity.In most of the countries where the expansion of cropland is merely impossible,agriculture automation has become the only option and is the need of the hour.Internet of things and Artificial intelligence have already started capitalizing across all the industries including agriculture.Advancement in these digital technologies has made revolutionary changes in agriculture by providing smart systems that can monitor,control,and visualize various farmoperations in real-time andwith comparable intelligence of human experts.The potential applications of IoT and AI in the development of smart farmmachinery,irrigation systems,weed and pest control,fertilizer application,greenhouse cultivation,storage structures,drones for plant protection,crop health monitoring,etc.are discussed in the paper.The main objective of the paper is to provide an overview of recent research in the area of digital technology-driven agriculture and identification of the most prominent applications in the field of agriculture engineering using artificial intelligence and internet of things.The research work done in the areas during the last 10 years has been reviewed from the scientific databases including PubMed,Web of Science,and Scopus.It has been observed that the digitization of agriculture using AI and IoT hasmatured fromtheir nascent conceptual stage and reached the execution phase.The technical details of artificial intelligence,IoT,and challenges related to the adoption of these digital technologies are also discussed.This will help in understanding how digital technologies can be integrated into agriculture practices and pave the way for the implementation of AI and IoT-based solutions in the farms.