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Published byAvice Henry Modified over 9 years ago
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Future PermaSense Challenges – Technology Jan Beutel
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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
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Competence in outdoor sensing Wireless systems, low-latency data transmission Customized sensors Ruggedized equipment Data management Planning, installing, operating (years) large deployments
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Established: deployment sites A. Hasler
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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
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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
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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
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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
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WORK IN PROGRESS – FUTURE CHALLENGES
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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
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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. Wirz S. Endrizzi / P. Limpach
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Next: high-resolution imaging Remote gigapixel panoramas as time-lapse movies 400’000-500’000 pixel (Nikon D300s @ 300mm)
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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.
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C2: Tomography/Performance Analysis Develop a set of tools/methods that allows to understand and learn from system behavior
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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…
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C4: Composition of Heterogeneous Systems We want to continue to scale and compose our systems from building block (with known properties)
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