A Review on Precision Agriculture Based on Robotic System

Abstract

Despite the challenges posed by the world's population growth, climate change, and labour shortage, agricultural robots offer a practical solution. The novel robotic system architecture outlined in this work led to the development of an advanced robot-based agricultural system which is an autonomous, multipurpose, and reasonably priced robotic platform for in-field plant high throughput phenotyping and precision farming. The use of robotics in the field of precision agriculture is considered one among the most challenging task in agriculture. The major objective of this project is to demonstrate how to create an intelligent robotic system that can collect and store data related to environmental parameters in real-time, such as leaf index, moisture content of the soil, and aerial image survey data, and send for classification and analysis on a web server. The process makes use of categorization, localization, object recognition, and segmentation machine learning techniques. A mobile app was developed in the Android Studio environment to track the images and transfer them to the webcam server.  The proposed model is integrated with a mobile-based application that smartphones can use to make quick, responsible decisions, enabling farmers to anticipate and prevent potential output losses by taking precautions in advance. For precision farming, a small-scale agricultural robot prototype was created and put to the test. The trial's outcomes show that it is capable of carrying out the essential responsibilities.