AIMC Topic: Agriculture

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Simulation of Transmission System of Crawler Self-propelled Rotary Tiller Based on Deep Learning.

Computational intelligence and neuroscience
Because of its good performance, crawler-type running gear plays a very important role in the fields of modern agriculture. This article aims to study the construction of the drive system of the crawler self-propelled rotary tiller with the deep lear...

Learning-Based Slip Detection for Robotic Fruit Grasping and Manipulation under Leaf Interference.

Sensors (Basel, Switzerland)
Robotic harvesting research has seen significant achievements in the past decade, with breakthroughs being made in machine vision, robot manipulation, autonomous navigation and mapping. However, the missing capability of obstacle handling during the ...

Vision-Based Module for Herding with a Sheepdog Robot.

Sensors (Basel, Switzerland)
Livestock farming is assisted more and more by technological solutions, such as robots. One of the main problems for shepherds is the control and care of livestock in areas difficult to access where grazing animals are attacked by predators such as t...

Recommendation of Business Models for Agriculture-Related Platforms Based on Deep Learning.

Computational intelligence and neuroscience
Agriculture is a basic and pillar industry. With the integration and development of Internet+, platform economy, and various industries, the business model of agriculture-related platforms is also constantly innovating. In this context, it is necessa...

Enriching IoT Modules with Edge AI Functionality to Detect Water Misuse Events in a Decentralized Manner.

Sensors (Basel, Switzerland)
The digital transformation of agriculture is a promising necessity for tackling the increasing nutritional needs of the population on Earth and the degradation of natural resources. Focusing on the "hot" area of natural resource preservation, the rec...

Optimization of Sample Construction Based on NDVI for Cultivated Land Quality Prediction.

International journal of environmental research and public health
The integrated use of remote sensing technology and machine learning models to evaluate cultivated land quality (CLQ) quickly and efficiently is vital for protecting these lands. The effectiveness of machine-learning methods can be profoundly influen...

The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence.

Animal health research reviews
Livestock welfare assessment helps monitor animal health status to maintain productivity, identify injuries and stress, and avoid deterioration. It has also become an important marketing strategy since it increases consumer pressure for a more humane...

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis.

PloS one
There is a dearth of literature that provides a bibliometric analysis concerning the role of Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this research gap and provides evidence from the studies conduc...

A Novel Interannual Rainfall Runoff Equation Derived from Ol'Dekop's Model Using Artificial Neural Networks.

Sensors (Basel, Switzerland)
In water resources management, modeling water balance factors is necessary to control dams, agriculture, irrigation, and also to provide water supply for drinking and industries. Generally, conceptual and physical models present challenges to find mo...

Climate Change Effects on Pathogen Emergence: Artificial Intelligence to Translate Big Data for Mitigation.

Annual review of phytopathology
Plant pathology has developed a wide range of concepts and tools for improving plant disease management, including models for understanding and responding to new risks from climate change. Most of these tools can be improved using new advances in art...