TY - GEN
T1 - Smart Environmental Monitoring Pilot
T2 - 15th IEEE Integrated STEM Education Conference, ISEC 2025
AU - Parra, Estefania Orjuela
AU - Saleh, Sam
AU - Mendoza, Kobe
AU - Paguio, Gabriel
AU - Rucker, Cassidy J.
AU - Shrestha, Sarahana
AU - Lal, Pankaj
AU - Zhu, Michelle
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This study investigates the impact of temperature and humidity on student well-being and productivity using a Raspberry Pi-based environmental monitoring system. Conducted as a pilot project within a single semester, this research deployed sensor kits across six different campus locations to collect real-time data on ambient temperature and humidity conditions. Simultaneously, a survey was administered to gather self-reported data on students' feelings and productivity in relation to the recorded environmental conditions. Utilizing chi-square tests to explore the relationships between these environmental factors and students' self-reported feelings and productivity, our findings indicate that while there are trends suggesting optimal environmental conditions, the results were not statistically significant due to the limited sample size and the brief data collection period. The study highlights the importance of moderate environmental conditions, with preliminary data suggesting that certain temperature and humidity levels may influence student comfort and cognitive performance. However, the lack of significant findings underscores the need for extended data collection over multiple seasons and with a larger cohort to enhance the reliability and generalizability of the results. This pilot project lays the groundwork for more comprehensive studies aimed at optimizing learning environments to support student success, emphasizing the importance of automating data collection processes and expanding the sample size to better understand the impacts of environmental variables on educational outcomes.
AB - This study investigates the impact of temperature and humidity on student well-being and productivity using a Raspberry Pi-based environmental monitoring system. Conducted as a pilot project within a single semester, this research deployed sensor kits across six different campus locations to collect real-time data on ambient temperature and humidity conditions. Simultaneously, a survey was administered to gather self-reported data on students' feelings and productivity in relation to the recorded environmental conditions. Utilizing chi-square tests to explore the relationships between these environmental factors and students' self-reported feelings and productivity, our findings indicate that while there are trends suggesting optimal environmental conditions, the results were not statistically significant due to the limited sample size and the brief data collection period. The study highlights the importance of moderate environmental conditions, with preliminary data suggesting that certain temperature and humidity levels may influence student comfort and cognitive performance. However, the lack of significant findings underscores the need for extended data collection over multiple seasons and with a larger cohort to enhance the reliability and generalizability of the results. This pilot project lays the groundwork for more comprehensive studies aimed at optimizing learning environments to support student success, emphasizing the importance of automating data collection processes and expanding the sample size to better understand the impacts of environmental variables on educational outcomes.
KW - Campus Climate
KW - Raspberry Pi Sensors
KW - Student Productivity
KW - Student Well-being
UR - https://www.scopus.com/pages/publications/105017751408
U2 - 10.1109/ISEC64801.2025.11147379
DO - 10.1109/ISEC64801.2025.11147379
M3 - Conference contribution
AN - SCOPUS:105017751408
T3 - 2025 15th IEEE Integrated STEM Education Conference, ISEC 2025
BT - 2025 15th IEEE Integrated STEM Education Conference, ISEC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 15 March 2025
ER -