Trailblazing Strategy: Implementing IoT-Powered Machine Learning to Identify Harmful Potatoes
摘要
The agricultural Internet of Things (IoT) has revolutionized agricultural output by improving productivity, quality of products, reducing labour costs, increasing farmer incomes, and modernizing agriculture. With agriculture consuming over 70% of freshwater and utilizing excessive chemicals, the need for efficient management of data and information is crucial in making timely decisions. To achieve a smart approach, farming needs to embrace new technologies to maximize inputs and improve production sustainability. By integrating IoT and communication technologies, farmers can efficiently manage soil tillage, agrochemicals, fertilizers, and water inputs to enhance profitability and output. The proposed control system using node sensors aims to detect poisoned potatoes while providing data management through smartphone and web applications. The system consists of hardware for collecting field data, a web application for data manipulation and analysis, and a mobile application for user control. This paper provides an overview of agricultural IoT, analysing its current state and system architecture.