1. 788.11J Presentation Landslide Prediction/Detection
Presented by Zhimin Yang
Presentation on the work of researchers at

2. Landslides
A landslide is an event where a block of earthen mass slides downhill covering the area underneath with dirt and debris.
Landslides are a major geologic hazard in the U.S
25 to 50 fatalities per year
$1B to $3B property damages

3. The main idea
Detect and estimate displacements before catastrophic event[1][2] for Finite Element Analysis Model to process
Use strain measurement to predict landslide[3]

4. System Architecture

5. Sensor column Stargate Gateway
Connected to peripherals placed at different lengths of a flexible tube
Geophones
Measure distance from seismic signal sources
Pore Pressure Transducer & Reflectometer
Measure positive and negative pressures and moisture content (si)–Strain
Gauges
Detect tube deformation
Other sensors are powered off until triggered by Strain Gage
Gateway is above ground rest of the column is below ground

6. The main achievements Landslide prediction system architecture
Landslide prediction algorithm[2]
Detection, Classification, Localization and Estimation
Threshold Based Detection and Statistical Detection Algorithms[3]
Centralized Vector Based Detection
Distributed Vector Based Detection with Independent Clusters
Distributed Scalar Based Detection with Independent Nodes
Distributed Vector Based Detection with Independent Nodes
Simulations[2][3]. Virtual landslide on 2-D virtual hill simulations[2] (more convincing).

7. The challenges Reliably detect and estimate small displacements
Determine columns that moved
Estimate new locations of dislocated columns
Estimate location of slip surface
3-D localization
Eliminate false alarms
(positive/negative)

8. Innovation New systems application
Can we simplify the system by using localization of sensor network? (without other types of sensors)

9. References
[1]Terzis, A.; Anandarajah, A.; Moore, K.; Wang, I.-J., "Slip surface localization in wireless sensor networks for landslide prediction," Information Processing in Sensor Networks, IPSN The Fifth International Conference on , vol., no.pp , April 2006
[2]A. N. Sheth, K. Tejaswi, P. Mehta, C. Parekh, R. Bansal,S. Merchant, T. N. Singh, U. B. Desai, C. A. Thekkath, and K. Toyama. Poster Abstract, A Sensor Network Based Landslide Prediction System. In Proceedings of Sensys 2005, Nov
[3]DISTRIBUTED DETECTION STRATEGIES FOR LANDSLIDE PREDICTION USING WIRELESS SENSOR NETWORKS, available at