This book presents the latest techniques for machine learning based data
analytics on IoT edge devices. A comprehensive literature review on
neural network compression and machine learning accelerator is presented
from both algorithm level optimization and hardware architecture
optimization. Coverage focuses on shallow and deep neural network with
real applications on smart buildings. The authors also discuss hardware
architecture design with coverage focusing on both CMOS based computing
systems and the new emerging Resistive Random-Access Memory (RRAM) based
systems. Detailed case studies such as indoor positioning, energy
management and intrusion detection are also presented for smart
buildings.