Abstract
This joint collaboration between the library, the Mechanical Engineering department shows the current research of localizing an Android smartphone using big data collection and sensor fusion techniques. The original work is Autonomous Indoor Localization via Field Mapping Techniques which primarily designed as indoor fire and safety aid.
For Agricultural Big Data Use, the Android smartphone is being applied to in indoor greenhouse fire, safety and data knowledge design. Such may aid big data tool value to greenhouse fire and safety design and any data that may be important fieldwork considerations.
The indoor agricultural mapping application may be application to greenhouses in indoor growing labs that promote educational and resource management capacity.For Big Data management we intend to utilize the CRIS (Figure 1) scientific workflow system and Purdue ionomic information management systems designed by Benjamin Branch, Peter Baker, Jia Xu, Elisa Bertino.
Keywords
big data, mechanical engineering, geospatial, data management, remote sensing
Date of this Version
3-5-2014
Recommended Citation
Cui, Yan; Ariyur, Kartik; and Branch, Benjamin D., "Autonomous Indoor Localization via Field Mapping Techniques, with Agricultural Big Data Application" (2014). Libraries Faculty and Staff Presentations. Paper 70.
https://docs.lib.purdue.edu/lib_fspres/70
Included in
Acoustics, Dynamics, and Controls Commons, Library and Information Science Commons, Other Mechanical Engineering Commons
Comments
This poster was presented at the Purdue University 2014 BIG Data in Agriculture Symposium, "Connecting Vision and Capacity," Wednesday, March 5, 2014.