Technological and Research Challenges in Data Engineering for Sustainable Agriculture

This paper presents a concise exploration of the evolving landscape of sustainable agriculture through the lens of data engineering. The aim is to highlight the most important challenges in the field and sketch ideas for how to address them. This position paper delves into key research challenges such as multi-modal data integration, data quality assurance, network optimisation and edge versus fog data processing strategies. Additionally, it emphasises the significance of performance enhancement in driving innovation within sustainable agriculture. By addressing these challenges and following the proposed visionary approaches for future research endeavours, we claim that data engineering will serve as a catalyst for advancing sustainable agriculture practices.