Smart Farming: Computer Simulation and Predictive Model for Cassava

Abstract

The widespread adoption of technologies has made digital transformation relevant to almost every sector of the economy, including agriculture. Thanks to technologies such as the Internet of Things (IoT), the farming industry now has access to tools that enable a shift from precision agriculture to farming. Smart farming has progressed from precision agriculture, which relied on technologies like satellites and planes for precise product applications, such as pesticides. These improvements allowed for the collection of information and assisting farmers at a reduced cost. The research examined farming architecture systems and their different levels. It introduced commonly used machine learning models in agricultural data management. By applying mathematical methodologies, a simulation model was created to study the growth of crops, particularly focusing on cassava as the plant of interest. Additionally, various machine learning models were constructed and evaluated using the available data.