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This book offers a comprehensive exploration of the transformative role that edge devices play in advancing Internet of Things (IoT) applications. Delving into the intricacies of traditional deep neural network (deepNet) approaches, the book addresses concerns about their energy efficiency during inference, particularly for edge devices.
Muhammad Arsalan received the M.Sc. degree in Computational Engineering from the University of Rostock, and the M.Sc. degree in Biomedical Computing from the Technical University of Munich. He is currently working as a Senior Data Scientist.
Introduction.- Background.- Signal Processing Chain with Spiking Neural Networks for Radar-based Gesture Sensing.- Radar-based Air-writing for Embedded Devices.- Time Series Forecasting of Healthcare Data.- Conclusion and Future Directions.