Test-Bed for Efficient Data Collection in Wireless Rechargeable Sensor Networks via Unmanned Vehicles

Undergraduate #348
Discipline: Technology and Engineering
Subcategory: Computer Engineering

Jamaal Roby - Texas Southern University
Co-Author(s): Miao Pan, University of Houston, Houston, TX Wayne Li, Texas Southern University, Houston, TX

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Energy consumption is an obstacle to various applications of wireless sensor networks (WSNs). This major drawback of WSNs is due to the long-distance multi-hop transmissions from the sensors to the sink. To address this issue, we employ multiple wireless charging vehicles (WCVs) to travel inside WSNs to replenish the energy of designated sensors while mitigating long -distance transmissions. Different from prior works, we let each WCV, not only, recharge the sensors, but also collect data from the sink, in coordination with other WCVs. This method allows nearby sensors to use short-distance transmissions to deliver their traffic to each designated sink while greatly increasing the lifetime of a WSN. We initially evaluated our idea with a small scale test-bed. 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 the P2110-Eval -01 development kit, Lego NXT Robots (NXT), and LabVIEW (LV). A program was then created in LV by guiding the NXT to follow a line guiding it to the sensor node via PID control. Battery capacity will be monitored by a virtual remote (VR) lab that was modified from existing project in the NSF CREST center at TSU. The VR lab will also have the capability to send any preprogramed commands to the WCVs. We have modified the VR lab to send/receive data and also created a program that allows the NXT to follow a line. Also, we are able to power a sensor via a 4.2v battery. Some critical findings during the implementation of the test bed were: 1) we were unable to charge a battery with our current equipment 2) charging a battery would also be more comprehensive than simply applying current 3) the NXT motors lacked efficient torque to support the weight of the transmitter and its power supply (PS) and 4) we would need a more effective method to locate the sinks on a larger scale. With respect to these challenges, we have devised possible solutions for each case. A battery management system would address the inability to charge a battery, and we ordered a WCV with stronger motors and added functionality. Furthermore, we will include location based services in the WCVs and sensor nodes. Future work will consist of full implementation of the VR lab, creation of a BMS and adding a method for locating nodes. A stronger WCV was purchased to carry the transmitter while permitting added control. We conclude that these steps would allow us to meet our objectives.

Funder Acknowledgement(s): The authors acknowledge that this research is supported in part by the National Science Foundation (NSF) under CREST program CNS-1350230, CNS1343361, NSF-1137732 and NSF-1241626.

Faculty Advisor: Wayne W. Li, liww@tsu.edu