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Federated Learning (FL) enables collaborative machine learning (ML) across distributed clients while preserving privacy. However, efficient model convergence in FL remains challenging, especially in wireless networks where non-independent and identically distributed (non-IID) data and frequent client dropouts are common. Traditional FL algorithms, such as FedAvg, rely solely on dataset size to weight client updates.

1. Introduction Soil moisture estimation, which involves quantifying the water content present in the soil, is a critical parameter in agriculture and crop management, as it directly influences various aspects of plant growth, health, and overall agricultural productivity. Soil moisture content is an essential indicator of water availability for plants.

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