The field of event classification and localization in building environments using accelerometers has grown significantly due to its implications for energy, security, and emergency protocols. Virginia Tech’s Goodwin Hall (VT-GH) provides a robust testbed for such work, but a reduced scale testbed could provide significant benefits by allowing algorithm development to occur in a simplified environment. Environments such as VT-GH have high human traffic that contributes external noise disrupting test signals. This paper presents a design solution through the development of an isolated platform for data collection, portable demonstrations, and the development of localization and classification algorithms. The platform’s success was quantified by the resulting transmissibility of external excitation sources, demonstrating the capabilities of the platform to isolate external disturbances while preserving gait information. This platform demonstrates the collection of high-quality gait information in otherwise noisy environments for data collection or demonstration purposes.
|