Smart Agricultural Drone with AI Pest Detection and Spraying Mechanism
Keywords:
AI in agriculture, Drone technology, Pest detection, Precision farming, SensorsAbstract
This paper presents the design and development of a smart agricultural drone integrated with artificial intelligence (AI) for real-time pest detection and automated pesticide spraying. The proposed system combines unmanned aerial vehicle (UAV) technology with computer vision and machine learning algorithms to enable efficient crop monitoring and precision farming. The drone captures high-resolution images of agricultural fields, which are processed using trained models to identify pest-infested regions with high accuracy. Based on the detection results, a targeted spraying mechanism is activated to apply pesticides only in affected areas, thereby reducing excessive chemical usage and minimizing environmental impact. The system is designed to operate autonomously, reducing manual intervention and improving operational efficiency in large-scale farming environments. Furthermore, the selective spraying approach optimizes resource utilization, lowers input costs, and enhances crop productivity. The integration of AI-driven decision-making with UAV-based monitoring demonstrates a scalable and sustainable solution for modern agriculture. The proposed approach contributes to the advancement of smart farming technologies by improving yield, ensuring environmental safety, and supporting data-driven agricultural practices.
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