Key Technology Research and Applications of Agricultural Inspection Robots Based on Machine Vision and Artificial Intelligence
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 63
Special Issue Editors
Interests: microclimate analytics of poultry houses; intelligent agricultural equipment; smart farming; non-destructive detection of meat quality; agricultural robot
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent agricultural equipment; three-dimensional reconstruction
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent agricultural equipment; disease detection
Special Issues, Collections and Topics in MDPI journals
2. Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: lake-atmosphere exchange
Interests: prediction model; computer simulation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the rapidly evolving realm of modern agriculture, machine vision (MV) and artificial intelligence (AI) have emerged as pivotal technologies, revolutionizing multiple agricultural sectors. For planting, agricultural inspection robots, equipped with high-resolution cameras and sophisticated environmental sensors, leverage MV to extract plant phenotypes, automate plant and organ detection, and gather real-time environmental data. Subsequently, AI algorithms analyze these data to build models, including convolutional neural networks for identifying diseases and pests and time series models for predicting plant growth. In livestock and poultry farming, MV and AI enable the continuous monitoring of animal behaviors, health status, and growth, thus facilitating early disease detection and optimized feeding strategies. In agricultural research laboratories, MV-based visual inspection systems, coupled with AI-driven gas detection sensors, ensure safety by detecting hazards, monitoring equipment operations, and alerting researchers to abnormal gas concentrations. The integration of MV and AI in agriculture promotes intelligent automation, reduces costs, enhances productivity, and reveals significant potential for the development of smart farming.
We are delighted to announce a new Special Issue focused on the cutting-edge research and applications of MV and AI in agriculture. Our research scope covers diverse topics, such as optimizing the visual systems of agricultural inspection robots for precise plant phenotyping and early pest detection in the planting industry; utilizing robotic MV and AI for livestock behavior analysis and health management; and deploying inspection robots integrated with MV and AI gas sensors to improve safety in agricultural research laboratories. We sincerely invite original research papers and comprehensive reviews to further explore and innovate in this vibrant field.
Dr. Xiuguo Zou
Dr. Yan Qian
Dr. Yuhua Li
Dr. Yong Wang
Dr. Wentian Zhang
Guest Editors
Manuscript Submission Information
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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
- machine vision
- artificial intelligence
- agricultural inspection robots
- agricultural sensors
- agricultural big data analytics
- behavior recognition of livestock and poultry
- plant phenotyping and pest detection
- agricultural laboratory safety and gas sensing
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