A novel warehouse monitoring framework based on UWB-IR

This paper introduces a novel framework to monitor warehouse with the adoption of Ultra Wide Band Impulse Radio (UWB-IR). In our framework, Empirical mode decomposition (EDM) and Hilbert Transform (HT) are combined to extract features with the motivation to raise the identification rate, and an improved Extreme Learning Machine (ELM) is taken as the classifier. By taking humans as the detection targets without considering the location, the experiment results demonstrated that our framework could implement warehouse monitoring in an efficient and low cost way.