190 likes | 297 Views
Future PermaSense Challenges – Technology. Jan Beutel. PermaSense. www.permasense.ch. 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. Competence in outdoor sensing.
E N D
Future PermaSense Challenges – Technology Jan Beutel
PermaSense www.permasense.ch • 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
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 A. Hasler 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
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
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 S. Endrizzi / P. Limpach 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. Wirz
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)