Development of a Machine Learning-Based Arduino Robot for Inline Seeding in Agriculture

Abstract

Increased demand for environment friendly and sustainable agricultural practices has accelerated the adoption of automation technology, in particular amongst small farmers. This paper affords the improvement of an Arduino-based multi-purpose agricultural robotic to operate key agricultural duties such as soil drilling, seed-planting and irrigation. The robot operates each in computerized and guide modes, chosen via Bluetooth, permitting flexibility in discipline operation. In computerized mode, the robotic follows the predefined sample of traces with the aid of the use of ultrasonic and infrared sensors to navigate and realize obstacles. The 775 motor-driven drilling mechanism, servo-controlled seed feeder and relay-activated water pump are the simple operation gadgets of the robot. In guide mode, all features can be managed remotely in actual time. The machine is powered through lithium batteries and managed through Arduino microcontrollers that combine sensor remarks and actuator control. The subject simulation validated excessive navigational accuracy, steady drilling and seedling depths, and correct water supply. The modular plan approves for future enhancements such as soil fitness monitoring, pest detection and adaptive fertilization. By automating labor-intensive tasks, the proposed robots will extend harvest yields, limit human labour, and guide extra sustainable agricultural practices. The lookup contributes to the boom of precision agriculture by means of supplying low-cost, custom-made and scalable robotic options for small-scale farmers.