Future PermaSense Challenges – Technology

Jan Beutel

PermaSense

• Consortium of several projects, start in 2006• Multiple disciplines (geo-science, engineering)• Fundamental as well as applied research• More than 20 people, 8 PhD students

www.permasense.ch

Competence in outdoor sensing•Wireless systems, low-latency data transmission•Customized sensors•Ruggedized equipment•Data management•Planning, installing, operating (years) large deployments

Established: deployment sites

A. Hasler

Established: rock/ice temperature

Aim: Understand temperatures in heterogeneous rock and ice

• Measurements at several depths• Two-minute interval, autonomous for several years• Survive, buffer and flush periods without connectivity

A. Hasler

Established: crack dilatation

Aim: To understand temperature/ice-conditioned rock kinematics

• Temperature-compensated, commercial instrument • Auxiliary measurements (temperature, additional axes,…)• Two-minute interval, autonomous for several years• Protection against snow-load and rock fall

Established: field site support• Base station

– On-site data aggregation – Embedded Linux– Solar power system– Redundant connectivity– Local data buffer– Database synchronization

• Cameras– PTZ webcam– High resolution imaging (D-SLR)

• Weather station

• Remote monitoring and control

Established: long-haul WLAN

• Data access from weather radar on Klein Matterhorn (P. Burlando, ETHZ)

• Leased fiber/DSL from Zermatt Bergbahnen AG

• Commercial components (Mikrotik)

• Weatherproofed

WORK IN PROGRESS – FUTURE CHALLENGES

New: acoustic emissions

Aim: To understand the importance that ice-segregation, volume expansion and thermal cycling have on rock damage in natural conditions – to infer instability zones.

• Continuous measurement, transmission of event statistics

• Storage of raw traces• Auxiliary data (temperature, moisture, camera,

… )

L. Girard

New: slope movement

Aim: To understand cryosphere-related slope movements based on their temporal patterns of acceleration and deceleration.

• Continuous GPS (years)• Daily fix (accuracy: few mm)• Auxiliary data (2 axis inclination, camera,

temperatures, … )• Several locations

V. WirzS. Endrizzi / P. Limpach

Next: high-resolution imaging

• Remote gigapixel panoramas as time-lapse movies• 400’000-500’000 pixel (Nikon D300s @ 300mm)

C1: Reliability – Predictability

Algorithms and system components MUST be designed in a way that allow a

deterministic result; even over a network ensemble with variable demand/resources.

C2: Tomography/Performance Analysis

Develop a set of tools/methods that allows to understand and learn from

system behavior

C3: Control of Complex Sensors

Constant rate sampling with static configurations was relatively easy. Non-

uniform rate sampling, variable resources & communication capabilities, multi-CPU architectures, disconnected operation…

C4: Composition of Heterogeneous Systems

We want to continue to scale and compose our systems from building

block (with known properties)