Cloud-Based AI Robotics for Precision Pruning of Fruit Trees to Improve Sustainable Farming

The crucial agricultural practice of precision pruning fruit trees greatly impacts fruit production yield and quality. Traditional pruning techniques take a lot of time and money because they need skilled workers and are labor-intensive. It suggests a novel cloud-based AI robotics system intended to precisely prune fruit trees to address these issues. This system uses cutting-edge robotics fitted with Convolutional Neural Networks (CNNs) to carry out precise and effective tasks related to pruning. Cloud computing integration makes it possible to process and make real-time decisions, improving the system's flexibility in responding to changing tree conditions and pruning needs. The system's primary parts are robotic arms for accurate cuts, various sensors for analyzing tree structures, and CNN models for maximizing pruning techniques. Early field trials show noticeable gains in operational efficiency and pruning accuracy compared to conventional techniques. This study demonstrates how cloud-integrated AI robotics can transform agricultural practices and improve fruit farming's sustainability and productivity.

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Published
2025-02-27
DOI
https://doi.org/10.1109/isacc65211.2025.10969274
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.75
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Cloud-Based AI Robotics for Precision Pruning of Fruit Trees to Improve Sustainable Farming

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Cloud-Based AI Robotics for Precision Pruning of Fruit Trees to Improve Sustainable Farming

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article en
1 citations

Abstract

The crucial agricultural practice of precision pruning fruit trees greatly impacts fruit production yield and quality. Traditional pruning techniques take a lot of time and money because they need skilled workers and are labor-intensive. It suggests a novel cloud-based AI robotics system intended to precisely prune fruit trees to address these issues. This system uses cutting-edge robotics fitted with Convolutional Neural Networks (CNNs) to carry out precise and effective tasks related to pruning. Cloud computing integration makes it possible to process and make real-time decisions, improving the system's flexibility in responding to changing tree conditions and pruning needs. The system's primary parts are robotic arms for accurate cuts, various sensors for analyzing tree structures, and CNN models for maximizing pruning techniques. Early field trials show noticeable gains in operational efficiency and pruning accuracy compared to conventional techniques. This study demonstrates how cloud-integrated AI robotics can transform agricultural practices and improve fruit farming's sustainability and productivity.

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), SRM Institute of Science and Technology (IN), Dr. M.G.R. Educational and Research Institute (IN), R.M.D. Engineering College, Saveetha University (IN)
Zero hunger
Openalex Percentile: Top 16%
Smart Agriculture and AI
1.75
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