Abstract
dc:description.abstractThe Goodwin Hall building on the Virginia Tech campus is the most instrumented building for vibration monitoring. It houses 225 hard-wired accelerometers which record vibrations arising due to internal as well as external activities. The recorded vibration data can be used to develop real-time applications for monitoring the health of the building or detecting human activity in the building. However, the lack of infrastructure to handle the massive scale of the data, and the steep learning curve of the tools required to store and process the data, are major deterrents for the researchers to perform their experiments. Additionally, researchers want to explore the data to determine the type of experiments they can perform. This work tries to solve these problems by providing a system to store and process the data using existing big data technologies. The system simplifies the process of big data analysis by supporting code re-usability and multiple programming languages. The effectiveness of the system was demonstrated by four case studies. Additionally, three visualizations were developed to help researchers in the initial data exploration.
Degree
thesis:*- Name thesis:degree_name
- Master of Science
- Level thesis:degree_level
- masters
- Discipline thesis:degree_discipline
- Computer Science and Applications
- Department dc:contributor.department
- Computer Science
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2019
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Kumar, Abhinav
- Chair dc:contributor.committeechair
-
- Fox, Edward A.
- Committee members dc:contributor.committeemember
-
- Tarazaga, Pablo Alberto
- North, Christopher L.
- Xie, Zhiwu
Subjects
dc:subject × 4Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Dc Identifier Other
- vt_gsexam:20567
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/101529