Abstract: This project involves designing and developing an autonomous robot for pesticide spraying in agriculture, aiming to enhance both the efficiency and precision of pesticide application. Traditional spraying methods can lead to uneven coverage and excessive chemical use, causing environmental harm and health risks. The proposed robot will leverage advanced machine learning algorithms to accurately identify and treat specific areas, reducing waste and optimizing coverage. The robot’s effectiveness will be evaluated through field tests, focusing on its precision, efficiency, and overall impact on crop health and yield
Keywords:
Here are the selected keywords:
Autonomous Robot
Pesticide Spraying
Precision Application
Efficiency
Machine Learning Algorithms
Economic Stability
L298N Motor Driver
Water Pump Motor
ESP32
Labor Costs
Safety and Health
Crop Yield
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