Semester of Graduation
Electrical and Computer Engineering
First Major Professor
Master of Science (MS)
This thesis presents a detailed look at channel state information (CSI), an efficient approach to the shape detection of physical objects, and observations on how environment noise affects CSI. CSI describes the communication link between a transmitter and receiver through the properties of multiple channels. Once analyzed, these channels or subcarriers describe how the signal travels from the transmitting device to the receiving device. While this information was intended to help increase signal quality and strength of a communication link, many other applications have been suggested.
The proposed application in this paper provides a way with minimal resources to capture and utilize CSI for shape detection. Instead of relying on gestures or movements, I focus on the experiment setup used to detect object shapes and their respective CSI signature. Hence, if I can determine the shape an object should be, then I can detect when that shape changes and capture specific events. In addition, I utilize Wi-Fi as a common source available to provide CSI in many real-world applications without the need for additional resources. Experimentally, I demonstrate how to build a system capable of capturing CSI, how to use CSI logging tools, how environment noise affects CSI, and an approach to detect shape changes.
Lopez, Andrew, "Shape detection of physical objects with Intel 5300 and the 802.11n CSI Tool" (2020). Creative Components. 526.