Exploring FarmBot in Agriculture Applications: An AI and IoT-Based Robotic System for Farmers with Disabilities

Abstract

Agriculture remains inaccessible for over 1.3 billion individuals with disabilities due to physical, sensory, and cognitive challenges, restricting their ability to perform tasks such as planting, irrigation, and weeding. FarmBot, an open-source Internet of Things (IoT) and artificial intelligence (AI)-based robotic system, can address these challenges by automating tasks such as planting and irrigation. Integrating IoT sensors, AI models, and an intuitive mobile interface empowers individuals with disabilities to engage in farming with reduced physical strain. This article examines FarmBot's architecture, highlighting specifically the weed detection system's high precision and recall. To integrate weed detection with high accuracy, a weed detection model has been trained achieving 95% precision, where it also explores the scalability of the platform for diverse applications, highlighting potential advancements such as voice controls and offline functionality, which aim to further enhance its accessibility and sustainability. The article also highlights challenges and future research directions in relevant areas.