Shivendu Mishra

FedHAttn: an attention-based homogeneous aggregation framework for energy-efficient and accurate PM2.5 prediction in IoAP-enabled edge devices

This work proposes FedHAttn, a novel hierarchical attention–based aggregation mechanism that explicitly models inter-client model feature importance to optimize global model performance and establishes an effective aggregator that balances accuracy, robustness, and efficiency in federated PM2.5 prediction.