TY - GEN
T1 - On the Design of an AI Enabled Edge Workplace Environment Monitoring Station
AU - Almeida, Esteban
AU - Sandoval, Diego
AU - Sánchez, Alberto
AU - Dávila, Pablo F.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper reports on the design of an AI enabled edge workplace monitoring system. The system measures fluctuations in temperature, humidity, CO2 levels and human traffic. The project integrates a Raspberry Pi 4 unit with sensors for measuring variables. A camera and an Intel Neural Compute Stick 2 are incorporated for image processing for future investigation of how human traffic impacts environmental variables and likewise how these variables affect human behavior. Notably, the system is self-powered by a solar panel to enhance sustainability and portability.
AB - This paper reports on the design of an AI enabled edge workplace monitoring system. The system measures fluctuations in temperature, humidity, CO2 levels and human traffic. The project integrates a Raspberry Pi 4 unit with sensors for measuring variables. A camera and an Intel Neural Compute Stick 2 are incorporated for image processing for future investigation of how human traffic impacts environmental variables and likewise how these variables affect human behavior. Notably, the system is self-powered by a solar panel to enhance sustainability and portability.
KW - AI
KW - environmental variables
KW - sustainability
KW - Wireless sensor network
UR - http://www.scopus.com/inward/record.url?scp=85211157912&partnerID=8YFLogxK
U2 - 10.1109/ARGENCON62399.2024.10735867
DO - 10.1109/ARGENCON62399.2024.10735867
M3 - Contribución a la conferencia
AN - SCOPUS:85211157912
T3 - 2024 7th IEEE Biennial Congress of Argentina, ARGENCON 2024
BT - 2024 7th IEEE Biennial Congress of Argentina, ARGENCON 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE Biennial Congress of Argentina, ARGENCON 2024
Y2 - 18 September 2024 through 20 September 2024
ER -