Harnessing Sensing, Artificial Intelligence, and Robotics for Digital Agriculture
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: 15 November 2025 | Viewed by 114
Special Issue Editors
Interests: computer vision; machine learning; 3D sensing; LiDAR sensing; automation; agricultural robotics
Special Issues, Collections and Topics in MDPI journals
Interests: agricultural robotics; plant phenotyping; machine vision; digital twin; automation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The integration of sensing, artificial intelligence (AI), and robotics into agriculture marks a transformative era in farming practices. Over the past two decades, advancements in these technologies have revolutionized traditional agricultural methods, thus enhancing productivity, sustainability, and efficiency. This journey began with the adoption of basic sensors for soil and crop monitoring, evolving into sophisticated AI-driven systems that are capable of predictive analytics and autonomous decision-making. Robotics has furthered this evolution, introducing automation in planting, harvesting, and maintenance tasks.
This Special Issue aims to explore the latest innovations in and applications of sensing, AI, and robotics in digital agriculture. We seek to provide a comprehensive platform for researchers, practitioners, and policymakers to share insights, challenges, and breakthroughs. The scope of this Special Issue encompasses a wide range of topics, including, but not limited to, precision agriculture, smart farming systems, autonomous machinery, and data-driven agricultural management.
We are particularly interested in cutting-edge research that presents novel methodologies, experimental results, and practical implementations, and welcome the submission of papers addressing interdisciplinary approaches that integrate agronomy, computer science, and engineering. Additionally, we explicitly invite works that propose validation procedures, operational standards for novel technologies, and economic analyses of the transition to digital agriculture. This Special Issue aims to foster a deeper understanding of how these technologies can sustainably transform agriculture, ensuring food security and environmental stewardship for future generations.
Dr. Md Sultan Mahmud
Dr. Lirong Xiang
Guest 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. Manuscripts can be submitted until the deadline. 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 special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy 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 2600 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.
Keywords
- smart farming
- agricultural robotics
- data-driven agriculture
- AI-enhanced farming, autonomous machinery
- crop monitoring
- IOT in agriculture
- digital twin
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