Exploring the Application of Artificial Intelligence and Image Processing in Agriculture

Dear Colleagues,

In recent years, the utilization of artificial intelligence (AI) technology has gained popularity across various sectors, including, but not limited to, robotics, education, banking, and agriculture. Advancements in sensing technologies, such as RGB-D, multi- and hyper-spectral, and 3D technologies, in conjunction with the proliferation of the Internet of Things (IoT), have enabled the retrieval of information across a wide range of spatial, spectral, and temporal domains. This, coupled with the integration of AI approaches, has led to the emergence of new insights and analysis. In particular, AI-powered computer vision technologies have become crucial in the development of intelligent and automated solutions. Within the agricultural sector, the implementation of AI has led to significant improvements in crop production and real-time monitoring, harvesting, processing, and marketing. Various hi-tech computer-based systems have been developed to determine important parameters such as weed detection, yield detection, and crop quality. However, it is essential to note that understanding and addressing the challenges related to safety and quality assessment for food production using AI technologies is a necessary step in realizing the full potential of these technologies within the agricultural sector. As such, this journal welcomes both fundamental science and applied research that describes the practical applications of AI methods in the fields of agriculture, food and bio-system engineering, and related areas.

The journal welcomes original research articles, review articles, perspective papers and short communications on the following topics of interest:

• AI-based precision agriculture;
• Smart sensors and Internet of Things;
• Agricultural robotics and automation equipment;
• Computational intelligence in agriculture;
• AI in agricultural optimization management;
• Intelligent systems for agriculture;
• Precision agricultural aviation;
• Expert systems in agriculture;
• Remote sensing in agriculture;
• AI technology in aquiculture;
• AI in food engineering;
• Automatic navigation and self-driving technology;
• Intelligent interfaces and human–machine interaction;
• Machine vision and image/signal processing;
• Machine learning and pattern recognition.

Dr. Yee Siang Gan
Prof. Dr. Sze-Teng Liong
Collection Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.