Every event that occurs has a reaction, whether it be a pebble causing ripples in a pond or a bullet distressing a wall. Within a structure, these vibrations caused by a specific event in a medium can be measured with an accelerometer, and just as the vibrations caused by a bullet differ observably from those caused by a pebble, vibrations caused by walking vary from those caused by falling, running or jumping. To the eye, these differences are slight to severe, but when that signal is dissected, it is identifiably unique by its cause and location with extensive applications from home security to commercial monitoring of foot traffic to behavior analysis for medical care including fall detection. The focus of this study was to investigate how this signal is collected -- specifically, if a cheaper independent computer could replace a setup that currently costs thousands. The Raspberry Pi was used with an ADXL345 accelerometer as this alternate system. This study includes notes of development of the hardware and software as well as analysis of the developed system by comparison to the accepted system. The new system is enabled to continuously read the accelerometer’s z axis output value, maintaining a buffer and saving significant signals. These hypothesized capabilities were confirmed by collecting vibration data from the same impact and comparing how each system recorded the event.
"Modelling Human Activity Through Structural Vibrations with Alternate Computational Devices to Increase Cost Efficiency,"
Journal of the South Carolina Academy of Science: Vol. 15
, Article 16.
Available at: https://scholarcommons.sc.edu/jscas/vol15/iss2/16