Discipline: Technology and Engineering
Subcategory: Computer Science & Information Systems
Jamaal Roby - Texas Southern University
Co-Author(s): Wei Wayne Li, Texas Southern University
The main pitfall of wireless sensor networks (WSN) is the amount of energy consumed during communication between nodes in the network. This weakness is exacerbated by the long distance, multi-hop transmissions back to the base station. In order to alleviate this problem, a test bed has been constructed to test the theory that the lifetime of a wireless sensor network can be extended with the use of the novel technology of Wireless Power Transfer (WPT) via unmanned vehicles (UV). A routing protocol will be employed to determine the specific nodes to be charged before each trip of the UV. This method greatly extends to life of a WSN. We initially evaluated our idea with a small scale test-bed that will be extensible to any size needed. The test-bed is focused on the idea of wireless charging (i.e., the ability to transfer electric power from one storage device to another without contact) using an evaluation module commercially developed to take advantage of WPT technology. The backend for the test bed is developed in LabVIEW which interfaces the WSN with a Virtual Remote (VR) lab that has been modified from a previous project. The VR lab will also have the capability to send any pre-programed commands to the WCVs. Battery capacity and the WSN environment will also be monitored by the VR lab. The VR lab will provide the ability to monitor the WSN anywhere that has an internet connection. The UV has also been modified to receive commands from the VR lab wirelessly. This is accomplished by installing custom firmware on a router that allows a wireless bridge to be created in order to communicate to/from the UV. Future work will consist of full implementation of the VR lab, creation of a BMS and adding a method for locating nodes. A more powerful UV was purchased to transport the transmitter while permitting added control. We conclude that these steps would allow us to meet our objectives.
Funder Acknowledgement(s): This work was partially supported by the National Science Foundation CREST Program under grant 1137732.
Faculty Advisor: Wei Wayne Li, LiWW@tsu.edu
Role: I conducted all research.