Satish Kukkapatnam, Vignesh Rajamani, Bradnon Lee Gardner, Jayjeet M. Govardhan, Andrew Contreras, Sharethram Hariharan
Oklahoma State University
Study of the origins of complicated patterns in sensor signals from manufacturing machines, processes, and specific infrastructure and lifeline systems and derive theory and methods to capture the dynamics underlying these signals for quality and integrity monitoring.
The proposed project leverages the recent multi-university (Oklahoma State, Penn State, MIT and Berkeley) grant from the National Science Foundation (NSF) on new wireless (RF) sensing technology. The advent of RFID and such technologies for asset and good tracking in warehousing and depot support operations has thrown new challenges to companies on: *How to best connect the various heterogeneous platforms and middleware to handle data, and *How to manage and harness the data for effective decision support so that ROI is maximized.
The deeper ramifications of these technologies for asset management and maintenance remain largely unexplored and untapped. The objective of the proposed project is to create a test-bed that serves companies to evaluate and benchmark critical data transmission (emission and receiving) and management techniques and practices in a non-commercial setting. The recently initiated NSF project will bolster the objectives of the proposed project in providing innovative physical testing platform, software and data management solutions.
A systematic statistical approach for experimental design of an RFID system was developed. Also the research has yielded new principles for harnessing information on the complex (nonlinear and stochastic) nature of the process underlying signals from RFID and other sensor networks.