Federated Learning Based Smart Horticulture and Smart Storage of Fruits Using E-Nose, and Blockchain: A Proposed Model

The main objective of this project is to increase the productivity of farmers producing fruits and vegetables in Kazakhstan. We are planning to use technology during production at orchards and also using technology during storage. At the production stage, we shall capture images of fruit flowers, growing fruits, and a ripe fruit. Then we shall apply federated learning to train our model with healthy fruits and flowers and then we shall be able to predict any ongoing pest infections with either fruits or flower. At the storage phase, we shall use e-nose to check the current status of apple and save it from any possible degradation. We shall also use blockchain to store data related to fruits at both stages of production and storage to create an e-passport that will give access to data related to production and storage of fruits. At the same time, we shall also use various width clustering algorithms to detect intrusion in our sensor based IoT networks.