Artificial Intelligence and Image Processing in Smart Agriculture
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 January 2026 | Viewed by 45
Special Issue Editor
Interests: robotics; agriculture; machine learning; deep learning; precision agriculture; crop monitoring and disease detection
Special Issue Information
Dear Colleagues,
This Special Issue is devoted to exploring the transformative role of artificial intelligence (AI) and image processing technologies in the domain of smart agriculture. As global agricultural systems face increasing demands for efficiency, sustainability, and resilience, intelligent solutions are becoming essential.
The primary aim of this Special Issue is to showcase recent advancements and innovative applications that leverage AI and image-based solutions to address real-world challenges in agriculture. We invite contributions from researchers, practitioners, and domain experts across multidisciplinary areas who are pioneering the use of these technologies to enhance productivity, reduce labor costs, monitor crop health, optimize resource utilization, and support decision-making processes.
We particularly encourage submissions that not only demonstrate technical innovation but also emphasize practical implementations and measurable impact on agricultural practices. This Special Issue aspires to serve as a comprehensive reference for ongoing research and to establish guidelines for future investigations in this rapidly evolving field. The topics of interest include, but are not limited to, the following:
- AI-based crop monitoring and disease detection using computer vision;
- Precision agriculture using UAV/drone imagery and remote sensing;
- Smart irrigation systems supported by AI and visual analytics;
- Yield estimation and prediction using deep learning models;
- Pest detection through image processing or artificial intelligence;
- Multispectral/hyperspectral image analysis for soil and crop health;
- Integration of IoT, AI, and imaging for real-time agricultural monitoring;
- Digital Twin models for simulating and optimizing agricultural operations
Dr. Muhammad Umer Khan
Guest Editor
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Keywords
- smart agriculture
- artificial intelligence
- deep learning
- image processing
- precision agriculture
- remote sensing
- crop monitoring
- pest and disease detection
- yield prediction
- hyperspectral imaging
- multispectral imaging
- smart irrigation
- agricultural robotics
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