TY - GEN
T1 - GLOF Monitoring System in High Mountain
T2 - 2025 IEEE Colombian Caribbean Conference, C3 2025
AU - Alvarado-Lugo, Robert A.
AU - Lujan-Leon, Jean P.
AU - Aguilar-Bueno, Jhean
AU - Silva, Guido
AU - De La Torre, Juan
AU - Obando, Luis Torres
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Glacier Lake Outburst Floods (GLOFs) pose significant risks in high-mountain regions, particularly for rural populations. However, the performance of real-time GLOF monitoring systems under varying meteorological conditions remains poorly understood. This study presents the development and evaluation of an IoT-satellite-based monitoring system designed for GLOF detection, with a specific focus on analyzing the impact of rainfall on data transmission latency. The system integrates rainfall and water level sensors, a CR1000X datalogger, and an ST6100 satellite transceiver, enabling automated data collection and transmission to the IsatData Pro web service. Preliminary results show that rainfall did not significantly affect latency (Spearman's ρ=0.007). In addition, the average latency was 22.9 seconds, with 95% of transmissions completed within 33 seconds, establishing a potential performance benchmark for similar systems. These findings support the refinement of real-time GLOF early warning systems.
AB - Glacier Lake Outburst Floods (GLOFs) pose significant risks in high-mountain regions, particularly for rural populations. However, the performance of real-time GLOF monitoring systems under varying meteorological conditions remains poorly understood. This study presents the development and evaluation of an IoT-satellite-based monitoring system designed for GLOF detection, with a specific focus on analyzing the impact of rainfall on data transmission latency. The system integrates rainfall and water level sensors, a CR1000X datalogger, and an ST6100 satellite transceiver, enabling automated data collection and transmission to the IsatData Pro web service. Preliminary results show that rainfall did not significantly affect latency (Spearman's ρ=0.007). In addition, the average latency was 22.9 seconds, with 95% of transmissions completed within 33 seconds, establishing a potential performance benchmark for similar systems. These findings support the refinement of real-time GLOF early warning systems.
KW - Data
KW - GLOF
KW - IoT
KW - Latency
KW - Monitoring
KW - Rain
KW - Satellite
UR - https://www.scopus.com/pages/publications/105033339976
U2 - 10.1109/C366505.2025.11340060
DO - 10.1109/C366505.2025.11340060
M3 - Articulo (Contribución a conferencia)
AN - SCOPUS:105033339976
T3 - C3 2025 - IEEE Colombian Caribbean Conference
BT - C3 2025 - IEEE Colombian Caribbean Conference
A2 - Gomez, Yesica Beltran
A2 - Mendoza, Paul Sanmartin
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 September 2025 through 20 September 2025
ER -