Blockchain and Deep Learning for Agricultural Advancement

The agriculture sector plays a significant role as it not only serves in meeting a substantial portion of worldwide food requirements but is also servers as one of the key contributors to the country's economy. However, some issues including economic inequality, unpredictability of weather patterns, and crop diseases seek for a solution which offers enhanced crop traceability and insurance automation to address food safety problems and financial difficulty. This study creates a prototype of a crop management system merging blockchain and deep learning technologies, assessing its practical aspects. Blockchain enhances data storage, traceability, and transparency, while deep learning boosts monitoring, disease detection, and crop recommendation. The proposed work demonstrates the system's advantages and hurdles thereby contributing to a more efficient and transparent crop management paradigm which aims to revolutionize the crop management system by adopting sustainable agricultural practices on a globally.