1. Collaboratively Adaptive Vibration Sensing System for High-fidelity Monitoring of Structural Responses Induced by Pedestrians
- Author
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Mostafa Mirshekari, Pei Zhang, Susu Xu, Hae Young Noh, and Shijia Pan
- Subjects
Engineering ,Heuristic (computer science) ,Clipping (signal processing) ,Geography, Planning and Development ,0211 other engineering and technologies ,Word error rate ,020101 civil engineering ,02 engineering and technology ,Signal ,structural vibration sensing ,0201 civil engineering ,lcsh:HT165.5-169.9 ,structural response monitoring ,High fidelity ,collaboratively adaptive sensing ,Clinical Research ,Distortion ,021105 building & construction ,Computer vision ,Built Environment ,High dynamic range ,indirect sensing ,business.industry ,Dynamic range ,Building and Construction ,lcsh:City planning ,Urban Studies ,lcsh:TA1-2040 ,pedestrian monitoring ,Artificial intelligence ,lcsh:Engineering (General). Civil engineering (General) ,business - Abstract
This paper presents a collaboratively adaptive vibration monitoring system that captures high-fidelity structural vibration signals induced by pedestrians. These signals can be used for various human activities’ monitoring by inferring information about the impact sources, such as pedestrian footsteps, door opening and closing, and dragging objects. Such applications often require high-fidelity (high resolution and low distortion) signals. Traditionally, expensive high resolution and high dynamic range sensors are adopted to ensure sufficient resolution. However, for sensing systems that use low-cost sensing devices, the resolution and dynamic range are often limited; hence this type of sensing methods is not well explored ubiquitously. We propose a low-cost sensing system that utilizes (1) a heuristic model of the investigating excitations and (2) shared information through networked devices to adapt hardware configurations and obtain high-fidelity structural vibration signals. To further explain the system, we use indoor pedestrian footstep sensing through ambient structural vibration as an example to demonstrate the system performance. We evaluate the application with three metrics that measure the signal quality from different aspects: the sufficient resolution rate to present signal resolution improvement without clipping, the clipping rate to measure the distortion of the footstep signal, and the signal magnitude to quantify the detailed resolution of the detected footstep signal. In experiments conducted in a school building, our system demonstrated up to 2× increase on the sufficient resolution rate and 2× less error rate when used to locate the pedestrians as they walk along the hallway, compared to a fixed sensing setting.
- Published
- 2023