Digital Twin for Sustainable Farming: Developing User-Friendly Interfaces for Informed DecisionMaking and Increased Profitability

This chapter endeavors to develop a robust digital model for farm optimization with the primary objectives of enhancing resource utilization, minimizing waste, and increasing productivity while mitigating environmental impact. The proposed digital twin will leverage data from diverse sources, including sensors, weather data, soil moisture levels, and crop yields. Methodologically, the integration and processing of this varied data will be achieved through advanced algorithms, ensuring a comprehensive and accurate representation of the farm. The simulation aspect of the digital twin will explore different scenarios, allowing for a nuanced understanding of the impact of interventions on farm productivity and sustainability. Specific scenarios, such as testing the effects of varied irrigation strategies on crop yields or optimizing fertilizer inputs, will be explored. Methodological considerations will be discussed, addressing challenges related to data integration, format disparities, and accuracy variations across different data sources. Crucially, collaboration with farmers and stakeholders will be a cornerstone of this research. Their insights and realworld experiences will be actively incorporated throughout the development process, ensuring that the digital twin is tailored to the practical needs and challenges faced in agricultural operations. In tandem with this, the development of user-friendly interfaces will be emphasized, providing farmers and stakeholders with accessible tools for interacting with the digital twin. Specific functionalities, tailored to inform periodic decisions and processes, will be integrated into the interfaces, fostering usability and adoption. The chapter will examine the assessment of environmental impact. A detailed examination of the criteria and indicators used to measure and minimize the farm's environmental footprint will be discussed. By addressing these methodological considerations comprehensively, this research aims to not only optimize resource use and reduce waste but also contribute to the transformative advancement of sustainable and efficient farming practices.