Optimization of Machinery and Agricultural Production Systems in Smart Farming

A special issue of AgriEngineering (ISSN 2624-7402).

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 590

Special Issue Editor


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Guest Editor
School of Plant and Environmental Sciences, Virginia Tech Blacksburg, Blacksburg, VA 24061, USA
Interests: robotics and automation for agricultural applications; machine systems and machines management for optimal equipment utilization; sensing systems and data analytics for precision agriculture

Special Issue Information

Dear Colleagues,

The demand for agricultural products is growing globally as the population increases. In response to this, agricultural production systems have undergone changes, particularly in machinery deployment and usage, in order to overcome the concerns of farm profitability and farming uncertainty.

The adopted techniques could be inspired by manufacturing methods—for example, studies investigating the optimization of agricultural processes with the application of the techniques of operations research. The integration of the lean principles and optimization for agricultural production systems encompasses crop rotation, the selection of planting sites/locations, growing fruits and vegetables, in-field traffic, etc. Such studies are important for agricultural planning for water/nutrient use, soil management, product demand, and crop life cycles and maturation, etc. 

Additionally, given the increased demand for the production and quality of agricultural products, focus could be placed on the optimization of agrotechnologies for smart farming. Unmanned aerial systems (UASs) and unmanned ground vehicles (UGVs), popularly known as drones and robots, respectively, are increasingly used in agriculture and livestock for monitoring, spraying, and tracking. For example, advancements in UAV technology in recent years have significantly reduced costs for crop yield estimations or pest detections.

In recent years, labor shortages have presented a challenge in the agricultural industry. This is, to a large extent, due to the underutilization of agricultural machinery. As such, it is critical for agricultural production systems to optimize the usage of agricultural machinery to overcome the labor shortage challenges and enhance the implementation of modern agricultural programs. One direction could be the development of decision support systems for production systems to determine the optimal configuration and number of utilized equipment—i.e., the equipment that is used for various agricultural operations, from planting to harvesting and post-harvest, required for the supply chain. The primary objective will contribute to the total operational cost of production systems and the completion of operations under time constraints. These factors also contribute to the development of models to describe the behavior of agricultural planning in strategic, tactical, and operational orientations.

Dr. Hasan Seyyedhasani
Guest Editor

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Keywords

  • unmanned ground vehicles
  • unmanned aerial vehicle
  • path planning
  • precision agriculture
  • wireless sensor networks
  • agricultural machinery management
  • simulations
  • mathematical models
  • smart farming
  • decision support system

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