AutomaticSelf Balancing Robot for Crop Monitoring

Abstract

The Automatic Self Balancing Robot for Monitoring of Crop is a novel robotic system designed for the agricultural industry to improve crop monitoring and management. The robot is equipped with sensors, cameras, and machine learning algorithms that enable it to navigate through fields, collect da-ta on plant health, and identify potential issues here in this case fruit ripening (Early ripe, partially ripe, Ripe and Decay) with the help of camera. The self-balancing feature of the robot allows it to operate on uneven terrain, ensuring stable and accurate data gathering. Data gathered by the robot such as tempera-ture, humidity and soil moisture are sent to a central system for analysis, ena-bling agricultural producers to decide on crop management. The use of this ro-botic system can increase productivity, reduce employment costs, and improve overall harvest yields PID control, a feedback control loop, modifies the robot's behaviors in response to the discrepancy between the desired and actual states. A mathematical process called Kalman filtering is used to calculate and remove noise from sensor measurements, enabling more precise data interpretation. To improve the overall impression of the robot's orientation, sensor fusion com-bines data from several sensors, such as gyroscopes and accelerometers. IMUs are sensor bundles with integrated sensors that provide information on rotation, acceleration, and magnetic field strength, allowing for accurate measurement and control.