Lubina, B., & Sundaram, R. (2024, March), Visualizing the Invisible: Object Detection via Wi-Fi Signal Mapping Emulation  Paper presented at 2024 ASEE North Central Section Conference, Kalamazoo, Michigan. 10.18260/1-2--45648

\bibitem{asee_peer_45648}
  Lubina, B., \& Sundaram, R. (2024, March), \emph{Visualizing the Invisible: Object Detection via Wi-Fi Signal Mapping Emulation}
  Paper presented at 2024 ASEE North Central Section Conference, Kalamazoo, Michigan.
  10.18260/1-2--45648

Benjamin Lubina and Ramakrishnan Sundaram.  "Visualizing the Invisible: Object Detection via Wi-Fi Signal Mapping Emulation".  2024 ASEE North Central Section Conference, Kalamazoo, Michigan, 2024, March.  ASEE Conferences, 2024.  https://peer.asee.org/45648 Internet.  12 Mar, 2025

\bibitem{asee_peer_45648}
  Benjamin Lubina and Ramakrishnan Sundaram.
  "Visualizing the Invisible: Object Detection via Wi-Fi Signal Mapping Emulation".
  \emph{2024 ASEE North Central Section Conference, Kalamazoo, Michigan, 2024, March}.
  ASEE Conferences, 2024.
  https://peer.asee.org/45648 Internet.  12 Mar, 2025

@INPROCEEDINGS{asee_peer_45648
author = "Benjamin Lubina and Ramakrishnan Sundaram"
title = "Visualizing the Invisible: Object Detection via Wi-Fi Signal Mapping Emulation"
booktitle = "2024 ASEE North Central Section Conference"
year = "2024"
month = "March"
address = "Kalamazoo, Michigan"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/45648}
number = {10.18260/1-2--45648}
}

TY  - CPAPER
AB  - This paper introduces a software tool designed to emulate and analyze Wi-Fi signal strengths from an array of ESP32 devices. This software serves as a companion piece to the already developed array and is meant to be integrated into the accompanying hardware setup. The primary goal of this tool is to create theoretical images of objects situated within the array by leveraging the variations in Wi-Fi signal strength caused by these objects. We present a comprehensive method that utilizes the unique properties of ESP32 microcontrollers to capture Wi-Fi signal metrics to generate a visual representation of the physical space and the object(s) within it. The inputs to this software mimic those provided by the hardware array and employs advanced algorithms to process the metrics made by the array. This technique, often referred to as Wi-Fi imaging or Wi-Fi based material sensing, has significant implications for various applications, including security, terrain mapping, navigation in visually impaired environments, and smart home systems. The results demonstrate the capability of our system to detect and visualize objects of different sizes and materials. Additionally, the paper discusses the challenges and limitations encountered during the research, such as signal interference and the resolution of generated images, as well as software limitations and integration challenges. Our findings suggest that this Wi-Fi based imaging approach, while still in its nascent stages, holds great potential for various practical applications. The paper concludes with future research directions, emphasizing the need for enhanced algorithms and more sophisticated ESP32 arrays to improve accuracy and resolution of the Wi-Fi imaging process.


AU  - Benjamin Lubina
AU  - Ramakrishnan Sundaram
CY  - Kalamazoo, Michigan
DA  - 2024/03/22
PB  - ASEE Conferences
TI  - Visualizing the Invisible: Object Detection via Wi-Fi Signal Mapping Emulation
UR  - https://peer.asee.org/45648
DO  - 10.18260/1-2--45648
ER  -