The data collected by Avacam‘s landslide monitoring sensors is processed using an advanced analysis system based on artificial intelligence and machine learning.
Each device is equipped with sensors that detect key variables such as ground inclination, temperature, and soil moisture.
This data is sent in real time to secure cloud platforms, where it is processed to identify any abnormal movements or variations that could signal an impending landslide.
Artificial intelligence plays a crucial role in analyzing this data, using predictive algorithms to detect patterns that precede a disaster.
These models are trained on historical data, which allows the system’s ability to identify risk signals to be continuously refined. The results of the analysis are then sent to operators, who receive timely alerts, enabling them to make quick and informed decisions.
By combining sensor technology with artificial intelligence, Avacam’s monitoring systems help transform raw environmental data into useful insights. This approach supports the early identification of unusual ground movements and helps operators understand changing conditions in landslide-prone areas.
Continuous data analysis also helps professionals monitor slope behaviour over time and respond to potential warning signs. By providing timely information about ground conditions, these systems support risk assessment and help professionals make informed decisions about landslide monitoring and prevention.
