Smart Power
MIT-Portugal (1.58) Test-bed
Indirect Consumption Monitoring using a WSN-based approach
Architecture
System Description
System based on a smart sensor network capable of monitoring and characterizing power consumption in a office. Sensor nodes collect data and send it to a server that preform some calculations in order to estimate appliances individual consumption.From this perspective, the use of indirect sensing monitoring becomes a major challenge and for the broadly adoption of such approach, it should be proved that is worth it. Moreover, the system provides through a simple web-interface, reliable data that can be downloaded and where it can applied different data models.
See also (EBLab poster)
Test-Bed Details
Images
Node #1 | Node #2 | Node #3 | Node #4 | ||||
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Test-Cases Description
Through the web-based user interface it’s possible to access the information about four test cases; each one has the goal of estimate the consumption of a single appliance. Next, we describe the role of each sensor node:
Node #1
Goal: Estimate the consumption of the Touch Media Center
How? Monitoring the appliance duty-cycle and Display
Sensors: Accelerometer, Light
Sensor Sampling Periods: 120 s, 50 s
Validation: Using an inline AC Power Meter
Node #2
Goal: Estimate the consumption of the HVAC
How? Monitoring indirectly the appliance different states
Sensors: Accelerometer, Temperature
Sensor Sampling Periods: 100 s, 50 s
Validation: Difference in the total consumption when it is in operation
Node #3
Goal: Estimate the consumption of the Desktop CPU
How? Monitoring indirectly the appliance internal state
Sensors: Accelerometer, Magnetometer, Temperature
Sensor Sampling Periods: 120 s, 50 s
Validation: Using an inline AC Power Meter
Node #4
Goal: Estimate the consumption of the Desktop Monitor
How? Monitoring indirectly the appliance duty-cycle
Sensors: Magnetometer, Temperature, Light
Sensor Sampling Periods: 40 s, 60 s, 120 s
Validation: Using an inline AC Power Meter
Links
Active period: Set. 2010 - Oct. 2011
GEMS team: David Possidónio