Post on 20-Mar-2017
transcript
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Autonomous Wireless Sensor Networks: from development to long term implementation Prof. Dr. Arturo Sanchez-Azofeifa1 (arturo.sanchez@ualberta.ca) Saulo Castro1, Mauricio Vega-Araya2
1. Alberta Centre for Earth Observation Sciences (CEOS) University of Alberta 2. Univesidad Nacional de Costa Rica
+Applications of some WSN in the literature
Application Location #,sensor,nodes Institution Year Duration Variables
Links,between,weather,&,hydrology:,catchment?scale,monitoring Hawaii not,given U,Hawaii 2008 7,months
water:,pH,,temp,,conductivity,,pO2,,turbidity,,water,level
Soil,water,contentAlmkerk,,Netherlands 18
Twente,&,Wageningen 2009 6,months
soil,moisture,(Decagon)
Climate,,broadly Amazon UNAMA 2006
Petrel,nesting Maine 32Intel,&,UC,Berkeley 2002 7,months
light,,temp,,IR,,RH,,barometric,pressure
Sediment Kansas 2 Kansas,State 2008 8,months opacity
Center?pivot,irrigation Texas 17 USDA 2008 1,month
IR,thermometer,for,canopy,temp,,air,temp,,RH,,solar,radiation,,windspeed,,rainfall
Traveling,irrigation Montana 5 USDA 2008 4,monthstemp,,RH,,wind,speed,,wind,direction
After MacGregor et al. 2013
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• Measurements at many spatial and temporal scales
• Changing data needs (usually sparse)
• Increased spatial coverage in heterogeneous environments.
• Synchronized sampling across sensors.
• Real-time data retrieval capabilities.
• Landscape scale remote sensing validation of biophysical products.
• Reduced human effort with increased information output.
• Non-intrusive!
Advantages of WSN in monitoring
+ Sensor Network Cyberinfrastructure
n Near real-time data management for Wireless Sensor Networks
n Simplified data/trend visualization
n Data mining: web data/metadata for cross-discipline social network research cooperation and analysis
Santa Rosa National Park, Environmental Monitoring Super Site, Guanacaste, Costa Rica: • 10 billion data points/year • CO2/H20 fluxes (vegetation and
soil) • Hyperspectral canopy
observations • Wireless Sensor Networks • On-line/Real time
communication via satellite technology
• Drone research • Micro-Satellite testing site
(AlbertaSat) • Atmospheric Sounding
calibration site • NASA Calibration/Validation site • Airborne and ground-based
LiDAR
+ Santa Rosa Environmental Monitoring Super Site: NEE and APAR from WSNs.
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2013
-161
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2013
-209
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2013
-257
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2013
-305
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2013
-353
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2014
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2014
-177
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2014
-225
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2014
-273
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2014
-321
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2015
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2015
-25
2015
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2015
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2015
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2015
-121
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2015
-169
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2015
-217
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2015
-265
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2015
-313
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2015
-361
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2016
-041
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2016
-089
FPA
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Terra MODIS v Environet FPAR Raw
MODIS FPAR Raw
Environet FPAR Score
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Santa Rosa Environmental Monitoring Super Site: FPAR MODIS Comparison
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MODIS TERRA MODIS AQUA
+Long term deployment of a WSN: Brazil, 10 –years (2006-2016).
Temperature/RH Photosynthetic Active Radiation (PAR)
+Final remarks: Challenges with Environmental WSNs
n Standardization
n Durability of Hardware
n Power Management
n Data Management!!!
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Current fact finding
Analyze data in motion – before it is stored
Low latency paradigm, push model
Data driven – bring the data to the query
Historical fact finding
Find and analyze information stored on disk
Batch paradigm, pull model
Query-driven: submits queries to static data
Traditional Computing Stream Computing
Query Data Results Data Query Results
Stream computing – Analyzing data in motion