This document describes an artificial intelligence system called "AI LANDSLIDE" that analyzes monitoring data to predict landslide velocity based on past inclinometric data and rainfall. It discusses applying the system to the Cassas Landslide in Italy, including input data used in the learning phase and accurate predictions of velocity data from 1998-2002 and displacement from 1991-2002. The document also mentions using the predictions to trigger civil protection alerts more reliably and studying mitigative measures like drainage tunnels. It concludes by noting the system could potentially be applied to predicting other natural phenomena beyond landslides.

1. AI Artificial Intelligence
Landslide Velocity Prediction
Applied to the Cassas Landslide, Italy

2. Table of contents
 Introduction
 Cassas Landslide
 Input data
 Velocity data prediction
 Past displacement prediction
 Mitigative measures
 Other applications
 End

3. Introduction
 "AI LANDSLIDE" analyses
monitoring data and allows
reliable predictions of landslide
velocity based on past inclino-
metric data and rainfall.
 Civil Protection Alerts can be
triggered with more reliability,
thus avoiding many costlycostly
crisis planning errorscrisis planning errors.

4. PARIS - LYON
GENEVA
TURIN - MILAN
GENOA - ROME

5. Cassas Landslide, Italy
 - Volume 20 - 30 million m3
- Lenght appx. 1.8 Km
- Average slope 50 to 55 %
- Slide depth appx. 60 m

6. Cassas Landslide
Rainfall 1998-2002

7.  The learning phase encompassed 40 points.
A.I. LANDSLIDE can already effectively
predict velocities after a rather short learning
phase!
Prediction: Velocity data 98-02

8. 1999
1999
2000
2000
2001
2001
2002
2002

9. Rainfall 1990-2002
 Rainfall data from 1991 to 2002 are available.
Thus it is possible to estimate the
displacement during this period

10.  AI Artificial Intelligence Landslide Prediction
Past displacement

11. ?

12. Displacement
 Real displacement Nov-98 to Ago-02
(46 months) Inclinometer n°3 ≈ 20.5 cm
≈ 20.5 cm
 Calculated displacement Jan-91 to Nov-98
(94 months) Inclinometer n°3 ≈ 21.1 cm
≈ 21.1cm

13.  According to the « AI Landslide » model the need of
implementing mitigative measures has clearly emerged. The
main scope being the depression of the ground water table
 Three alternatives have been studied with a risk management
approach:
 Deep drainage by vertical shafts and submerged
pumps
 600 m long tunnel in stable ground with ascending
drainage boreholes
 150 m long 3 x 3 m drainage tunnel in the
sliding mass with subhorizontal drains
« AI Landslide » engineering
application

14.  The system « AI Landslide » can be custom tailored to study
other events and phenomena than landslides.
 Practically, any activity in which the driving parameters can be
measured and identified can be studied with « AI Landslide ».
However the model has to be custom tailored for each
phenomenon:
 - Levels of water in a river or creek
 - Deformations and settlements
 - Tunnel’s convergence
 - Rock mass movements
 - Dispersion of contaminants
 - Etc.
Other « AI Landslide » applications

15. END
 More information in:
 www.ailandslides.com
 www.riskope.com