smart farming

Aim:

          The aim of this research is to develop a secure, scalable, and privacy-preserving architecture for smart farming systems by integrating blockchain, federated learning, and ensemble learning techniques to enhance the detection of external intrusions while ensuring data authenticity, confidentiality, and decentralized decision-making.