Monitoring System Warning of the Collapse of Steep Slopes

[INQ. NO. 2203E16] IssaLab’s OWL system calculates impulse, moving average, inclination, etc. through a compound sensor for measurement of steep slopes, classifies the danger of certain steep slopes according to safe, attention, caution, and alarm. It can thus help ensure preemptive action is taken by supplying information on dangerous steep slopes.
This system is very suitable for steep slopes on expressways, steep slopes on railroads, and dangerous rocks and landslides on national park trails.

All the disasters generate so-called herald signals. The timely exercising of preemptive response strategies is an approach to minimize damage by detecting and interpreting the micro flux that cannot be recognized and then assist decision-making of the danger. The Owl system is what is called a forecasting system for disaster-free safety, which is helpful for preemptive response before the occurrence of damage by detecting warning signs that cannot be recognized on a real-time basis.
The Owl system installed and operated on the slopes of the nation’s expressways showed 62.5 percent effectiveness in preemptive response. In 2021, the system displayed more than 75 percent effectiveness in preemptive response through intelligentizing the algorithm with the support of Disaster Management Institute. IssaLab does its utmost to improve its product by applying A.I machine-learning with an aim to accomplish more than 80 percent in the effectiveness of the preemptive response by 2022.

The Owl system goes beyond the existing ways of monitoring of steep slope collapses, by supplying what is called ‘intelligent decision-making information’ by analyzing and interpreting the warning signs that occur before the collapse by monitoring from at least 100 times to up to 200 times per second of on the micro flux on the shock, tilt, and vibration generated from the inner part of the steep slope.
In addition, as the wireless operation platform utilizes 4G networks and LoRa networks, the user can rationally make a decision on the network operation in consideration of the generated amount and transmission speed of data.
 
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