Blockchain based Agriculture Using the Application of UAV and Deep Learning Technique: Alexnet CNN

Abstract

Due to the warm and humid environment of Bangladesh, it is highly exposed to occurring perpetuation of various viruses which cause diseases in crops. A huge number of crops are wasted because of these occurring diseases and it directly hurts the production rate and forces import of crops in bulkier amount. Unmanned aerial vehicle usage is one of the smart agriculture technologies being researched for agricultural applications (UAVs) in these days. UAV technology allows farmers to quickly gather information on field conditions by providing overhead images of their agricultural fields or even allowing them to zoom in on a particular area. Using UAV technology, farmers may identify specific areas that need immediate attention and perform the necessary agricultural improvements. Drones collect data that farmers can use to detect crop disease by applying deep learning algorithms to make long-term decisions about planting, land mapping, damage control, and other things. This research uses blockchain technology to establish connection between suppliers and customers by enabling information to be tracked throughout the supply chain and enhances food supply chain safety. It offers a secure method of broadcasting data, focusing on enhancement of supply chain management and prediction of crops which makes it possible to implement and deploy data-driven technologies for smart farming. The research uses UAVs as a means of collecting crop images, implements a prediction model using AlexNet CNN and analyses how it performs with a real Bangladeshi crop disease dataset to help farmers from excessive crop damage. Furthermore, the overall process is carried out using the Blockchain technology to enhance the existing supply chain management process.