Hur, B., & Pan, Z., & Price, K., & Aguado, F., & Gavlick, J., & Kim, S., & Kim, E. J., & Myles, K., & Adelman, Z. (2022, August), Low-Cost Raspberry Pi Compute Module 3+ Cluster for Mosquito Research via Capstone Project  Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41189

\bibitem{asee_peer_41189}
  Hur, B., \& Pan, Z., \& Price, K., \& Aguado, F., \& Gavlick, J., \& Kim, S., \& Kim, E. J., \& Myles, K., \& Adelman, Z. (2022, August), \emph{Low-Cost Raspberry Pi Compute Module 3+ Cluster for Mosquito Research via Capstone Project}
  Paper presented at 2022 ASEE Annual Conference \& Exposition, Minneapolis, MN.
  10.18260/1-2--41189

Byul Hur, Zhihao Pan, Kevin Price, Fernando Aguado, Jonathan Gavlick, Sungkeun Kim, Eun Jung Kim, Kevin Myles, and Zach Adelman.  "Low-Cost Raspberry Pi Compute Module 3+ Cluster for Mosquito Research via Capstone Project".  2022 ASEE Annual Conference & Exposition, Minneapolis, MN, 2022, August.  ASEE Conferences, 2022.  https://peer.asee.org/41189 Internet.  04 May, 2024

\bibitem{asee_peer_41189}
  Byul Hur, Zhihao Pan, Kevin Price, Fernando Aguado, Jonathan Gavlick, Sungkeun Kim, Eun Jung Kim, Kevin Myles, and Zach Adelman.
  "Low-Cost Raspberry Pi Compute Module 3+ Cluster for Mosquito Research via Capstone Project".
  \emph{2022 ASEE Annual Conference \& Exposition, Minneapolis, MN, 2022, August}.
  ASEE Conferences, 2022.
  https://peer.asee.org/41189 Internet.  04 May, 2024

@INPROCEEDINGS{asee_peer_41189
author = "Byul Hur, Zhihao Pan, Kevin Price, Fernando Aguado, Jonathan Gavlick, Sungkeun Kim, Eun Jung Kim, Kevin Myles, and Zach Adelman"
title = "Low-Cost Raspberry Pi Compute Module 3+ Cluster for Mosquito Research via Capstone Project"
booktitle = "2022 ASEE Annual Conference \& Exposition"
year = "2022"
month = "August"
address = "Minneapolis, MN"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/41189}
number = {10.18260/1-2--41189}
}

TY  - CPAPER
AB  - Mosquitos might have caused approximately seven hundred thousand deaths per year. Monitoring environmental factors for potential breeding sites of mosquitoes is an important and effective method in mosquito control. Several networks and systems for mosquito research have been developed in academic settings. For the research in this paper, the developmental progress of a low-cost data server and the network in the form of an IoT (Internet of Things) system with undergraduate engineering students is presented. A low-cost data server was proposed as one of the IoT system implementations for mosquito research. This low-cost cluster framework will be presented in this paper, which consists of multiple low-cost Raspberry Pi boards. A cluster was formed using four customized Raspberry Pi compute module 3+ (RPi CM3+) boards. In addition, the low-cost data server consists of a network switch, a custom interface PCB, and an enclosure. The network switch provides communication between the RPi CM3+ boards. The interface PCB was designed to provide power to the custom RPi CM3+ boards. An enclosure with a fan was designed and fabricated to secure all these boards and provide cooling to the system. Using this RPi cluster platform, a micro-Kubernetes cluster has been configured. One of the RPi CM3+ boards is configured as a master node, and the other CM3+ boards are configured as worker nodes. An Android application has been under development to access the data for the IoT cluster data server. The prototype cluster device was created by a capstone team at Texas A&M University. The capstone team was created in Fall 2020, and the capstone project was concluded in Spring 2021. Further research and development on this RPi cluster for mosquito research is in progress in the Dr. Hur’s research group by one of the students who joined the graduate degree program. 
AU  - Byul Hur
AU  - Zhihao Pan
AU  - Kevin Price
AU  - Fernando Aguado
AU  - Jonathan Gavlick
AU  - Sungkeun Kim
AU  - Eun Jung Kim
AU  - Kevin Myles
AU  - Zach Adelman
CY  - Minneapolis, MN
DA  - 2022/08/23
PB  - ASEE Conferences
TI  - Low-Cost Raspberry Pi Compute Module 3+ Cluster for Mosquito Research via Capstone Project
UR  - https://peer.asee.org/41189
DO  - 10.18260/1-2--41189
ER  -