Artificial Intelligence Applications in Precision Agriculture
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 February 2026 | Viewed by 392
Special Issue Editors
Interests: precision agriculture; remote sensing; UAV imagery; artificial intelligence; robotics
Interests: precision agriculture; unmanned aerial systems; imagery analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Precision Agriculture (PA) has been transforming agricultural production by introducing more advanced methods for collecting, analyzing, and interpreting data to better understand field variability. In this context, Artificial Intelligence (AI) plays a pivotal role by enhancing each stage of the process, enabling more accurate, efficient, and representative data collection, analysis, and decision making. Notably, AI facilitates real-time decision making, addressing one of the key challenges in PA. In short, advancements in AI and PA are driving the future of agricultural production, enhancing safety, improving quality, and fostering greater trust among stakeholders across the agricultural value chain. Consequently, this Special Issue aims to highlight recent innovations in AI-driven applications within precision agriculture. Topics of interest include, but are not limited to, machine learning, deep learning, natural language processing (NLP), and the integration of the Internet of Things (IoT) with AI systems. We also welcome contributions that explore the integration of cutting-edge technologies such as unmanned aerial vehicles (UAVs), robotics, hand-held sensors, satellite systems, and imaging technologies.
Dr. Marcelo Barbosa Júnior
Dr. Paulo Flores
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- automation
- computer vision
- decision support systems
- digital agriculture
- field management
- precision agriculture
- predictive models
- remote sensing
- smart farm
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