Trust-based decentralized blockchain system with machine learning using Internet of agriculture things

The growth of Internet of Agriculture Things (IoAT) with wireless technologies has resulted in significant advances for smart farming systems. However, various techniques have been presented to predict the soil and crop conditions. Nonetheless providing a quality-enabled autonomous system is one of the important research challenges. Furthermore, in the event of network over-loading, most existing work needs help to handle trustworthy communication. As a result, this paper proposes a smart optimization model to develop reliable and quality-aware sustainable agriculture using machine learning. Firstly, the proposed model utilizes intelligent devices to automate the data collection and transmission. It analyzes the independent performance variables to support the consistent decision-making process for the forwarding scheme. Secondly, the proposed model investigated blockchain-based security principles for integrating the trusted system to reduce communication interference. The proposed model has been validated through simulations, and numerous experiments have demonstrated its efficacy regarding network parameters.