Advanced Agriculture Machines and Technologies in Smart Farming

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 464

Special Issue Editor


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Guest Editor
Natural Resources Institute Luke, Helsinki, Finland
Interests: field robots and drones; sensors for fields and PLF; AI for farm management

Special Issue Information

Dear Colleagues,

The integration of smart machines in the agricultural sector enhances the efficiency of food production, making it more sustainable and profitable, while decreasing the negative environmental impact. Smart farming benefits from the rapid development of IT in collecting and processing data and decision making. However, the specificity of the agricultural environment and farm management limits the actual implementation of smart machines in fields.

Most farms worldwide are small companies that cannot afford large investments in new technologies without being certain of the future profitability. Existing smart machines usually have a narrow specialization, have a high cost, and are only applicable during short periods of time, which means they are only efficient in specific cases and conditions. In addition, safety regulations for autonomous machines usually require the presence of a human observer close to the machines.

The agricultural environment is still challenging for the current level of AI, and in most cases, human workers perform perception tasks better than robots. Moreover, field robots are usually used in an unfitted environment with a high level of plant diversity, which complicates the machine's functioning.

Barn robots have been successfully integrated, particularly due to the regularized working environment they are used in. However, many tasks in animal farms, both indoors and outdoors, still require automation through smart machines.

The objective of this Special Issue is to advance the agricultural sector to the next technological level by developing new methods and machines, as well as facilitating the effective integration of existing machines.

Dr. Victor Bloch
Guest Editor

Manuscript Submission Information

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Keywords

  • field robots and drones for actuating
  • new tasks performed by autonomous machines
  • human–robot collaboration in field tasks
  • robot swarms in field tasks
  • infrastructure for robot autonomy in fields
  • low-cost platforms for commercial use
  • economic considerations in using smart farm machines
  • safety issues in field robot autonomy
  • fitting plants and the growing environment to machines
  • robotics in PLF

Published Papers (1 paper)

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Research

19 pages, 9014 KiB  
Article
Performance Optimization and Simulation Test of No-Tillage Corn Precision Planter Based on Discrete Element Method (DEM)
by Jingyu Yang, Hailong Wu, Anfu Guo, Regis Rugerinyange, Chang Liu, Zhengyu Zhao, Wenchao Han and Lvfa Yin
Machines 2024, 12(7), 465; https://doi.org/10.3390/machines12070465 - 10 Jul 2024
Viewed by 196
Abstract
In order to test the influence of the structural design of a no-tillage corn precision planter on vibration stability performance, a vibration model was constructed with the help of MATLAB/Simulink, and it was concluded that the vibration response curve of the no-tillage corn [...] Read more.
In order to test the influence of the structural design of a no-tillage corn precision planter on vibration stability performance, a vibration model was constructed with the help of MATLAB/Simulink, and it was concluded that the vibration response curve of the no-tillage corn precision planter was relatively smooth. Based on the theory of the discrete element method (DEM), taking the planting apparatus of the no-tillage corn precision planter as the research object, firstly, a DEM single-factor test was carried out to investigate the effects of the slot inclination angle, number of slots, and rotational speed of the planter plate on the disturbance performance. Then, a three-factor, three-level orthogonal test was conducted with the maximum amount of seed discharging, the minimum average speed, and the minimum average kinetic energy as the final optimization objectives, and the qualified rate of seed discharging and the leakage rate as the evaluation indexes. The results show that the larger the inclination angle, the higher the number of slots, and the faster the rotational speed, the more violent the particle disturbance. At the same time, when the slot inclination angle of the planter plate is 60°, the number of slots is 20, and the rotational speed is 55 rpm, the seed discharge efficiency is the highest, at this time, the seed discharge qualification rate of maize particles is 95%, and the leakage rate is 3%; the results of this test can provide technical support for the research of the same kind of precision sowing equipment in the future. Full article
(This article belongs to the Special Issue Advanced Agriculture Machines and Technologies in Smart Farming)
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