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Introduction <p>The agricultural community has seen remarkable development in recent times with the introduction of advanced tools that are intended to improve productivity and sustainability.</p> Objective <p>This research investigates how new technologies respond to main issues in precision agriculture, such as hill farming, by adopting automation and data-based solutions.</p> Method <p>The study points out that drone sprayers can cut the use of pesticides by 30–50%, resulting in 60% pesticide drift reduction, and yield increase of 12–20% based on crop type and landscape. Autonomous navigation systems enhance work efficiency, saving labor costs by 40–60% and maximizing input utilization. Image processing also increases the accuracy of decision-making by 85% based on real-time analysis of field conditions and crop health. The convergence of these technologies not only improves accuracy but also reduces environmental effect by conserving 40–50% of water consumed in spraying processes.</p> Conclusion <p>This review integrates current knowledge using case studies and experimental results, addressing regulatory issues, technical hurdles, and future developments. Through the examination of the collective effect of drone sprayers, autonomous navigation, and image processing in various agricultural environments, this research highlights the revolutionary potential of precision agriculture in enhancing productivity, sustainability, and cost-effectiveness.</p>

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Precision Farming with Drone Sprayers: A Review of Auto Navigation and Vision-Based Optimization

  • 期刊论文

  • 发表日期：

    2025年5月7日

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  • Sanjeet Kumar Borah,
  • Mrutyunjay Padhiary,
  • Laxmi Narayan Sethi,
  • Avinash Kumar,
  • Pranjal Saikia

摘要

Introduction

The agricultural community has seen remarkable development in recent times with the introduction of advanced tools that are intended to improve productivity and sustainability.

Objective

This research investigates how new technologies respond to main issues in precision agriculture, such as hill farming, by adopting automation and data-based solutions.

Method

The study points out that drone sprayers can cut the use of pesticides by 30–50%, resulting in 60% pesticide drift reduction, and yield increase of 12–20% based on crop type and landscape. Autonomous navigation systems enhance work efficiency, saving labor costs by 40–60% and maximizing input utilization. Image processing also increases the accuracy of decision-making by 85% based on real-time analysis of field conditions and crop health. The convergence of these technologies not only improves accuracy but also reduces environmental effect by conserving 40–50% of water consumed in spraying processes.

Conclusion

This review integrates current knowledge using case studies and experimental results, addressing regulatory issues, technical hurdles, and future developments. Through the examination of the collective effect of drone sprayers, autonomous navigation, and image processing in various agricultural environments, this research highlights the revolutionary potential of precision agriculture in enhancing productivity, sustainability, and cost-effectiveness.