The application of Internet of Things (IoT) and Machine Learning (ML) to the agricultural industry has enabled the development and creation of smart farms . The growth in the number of smart farming has given rise to the CooperativeSmart Farming (CSF) where different connected farms collaborate with each other and share data for their mutual benefit . However, some of the farms do not transfer high-quality data and rely on other farms to feed ML models . Another possibility is the presence of rogue farms in CSFs that want to snoop on otherfarms without actually contributing any data . In this paper, we analyze the behavior of farms participating in CSF using game theory approach, where eachfarm is motivated to maximize its profit . We propose a MLframework that segregates farms and automatically assign them to an appropriate CSF cluster based on the quality of data they provide . Our proposed model . We first present the problem ofdefective farms inCSF . We then propose a model that segregate farms and then propose to segregates them to CSF . Our proposal is to ensure the model . It also proposes a model to penalize the farms supplying better data and to ensure a model of CSF that does not provide required data or are malicious in nature, and to solve the defective farmsproblem. Our proposed

Author(s) : Deepti Gupta, Paras Bhatt, Smriti Bhatt

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Keywords : farms - data - model - csf - smart -

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