Author

Teodoro Montanaro

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Open access 2026

Evaluation of Deep Learning Architectures on Synthetic LiDAR Sequences for Fall Detection

The study evaluates four temporal deep learning models including LSTM, GRU, CNN1D and Transformer Lite to analyze spatio temporal motion patterns from 3D LiDAR point sequences and identify the most suitable approach for accurate fall detection.

Amir Ali, Teodoro Montanaro, Ahmad Alsharoa et al. · IEEE Access · 0 citations

Conference Jul 2026

Online Federated Learning on Resource-Limited IoT Devices for Traffic Flow Prediction in Smart Mobility Ecosystems

Traffic congestion significantly impacts safety and urban livability in smart cities, motivating the development of accurate Traffic Flow Prediction (TFP) systems. Traditional deep learning approaches typically rely on centralized training, which is difficult to scale in distributed Internet of Things (IoT) environment...

M. Pizzolante, A. Shumba, T. Montanaro et al. · Annual International Compute... · 0 citations