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Energy-efficient operation of GSM-
connected infrared rodent sensor
Gábor Paller, paller.gabor@sze.hu
Gábor Élő, elo@sze.hu
Széchenyi University, Győr
2016 February 19
Precision agriculture and the
agrodat.hu project
• Precision
agricultural
management
• Better control of
production risks and
costs
• Information systems
supporting
decisions
3
Crop production
AgroDat.hu project
Main objective: Establish an
agricultural knowledge centre
and decision support system
• based on data gathered by an
innovative, complex sensor
system and from international
open repositories
• relying on big data, cloud, and
HPC technologies
to support precision agriculture.
Duration: 2014-2017
Budget: 2.4 Mrd HUF (appr. 8
MEUR)
URL: www.agrodat.hu
Consortium:
Local
Senso
r
Globa
l
• Information about environmental and
vegetation processes (supplied off-line)
• Sensors and data capture tools
• Data processing system
• Visualization
• Decision support
5
Elements of the agricultural
decision support system
Sensor lineup
l
2014 – soil and environmental sensors
with simple scalar output – done
l
2015 – camera sensors in multiple
wavelengths with simple and intelligent
triggers – research phase completed,
field-ready implementation in progress
l
2016 – making the camera sensor
mobile
Soil sensor
8
Proposed system architecture
Sensor unit
Sensor
control
Network
Communication
+
App. logic
(Telit GL865)
Data server
GPRS/HTTP POST
requests
WSGI
HTTP server
Database
adapter
Data
visualization
SMSC
End user
Mobile
network
SMS
HP DSM
(Dynamic SIM Management)
SMPP
4.3+
Sensor management
server
Management
user
Server farm
Camera sensor
development
Camera sensors
l
Mission: observe plants and pests in
wide frequency spectrum (visible and
invisible)
l
Simple case: take a series of pictures
and videos at given time spots and
upload them to the server
l
More complicated: detect an event of
interest and upload only if something
interesting is happening
Camera sensor development
l
Use case: common
vole detection
l
Overpopulation due
to mild winters
l
2014 damage
estimation: 500000
tons only in winter
wheat
l
Night animal: cameras in different
wavelength are needed (short-
wavelength infrared and long-
wavelength infrared are being tried)
l
Energy consumption: send images
only if there's high chance of having
animals in the picture → image
processing on the sensor
Advantages of the use case
Common vole in short-
wavelenght infrared
Animal
Common vole in long-wavelenght
infrared
Dynamic mapping to 256-level
greyscale image
Image processing in the sensor
l
Image thresholding – 80% static threshold
l
Get rid of spurious patches – contour
tracing+convex hull filling
l
Close gaps - dilating by a kernel of 6x6
l
Calculate circles of interesting objects –
contour tracing+enclosing circles
l
Find out if the circles move – match the
circles with the circles on the previous
image and flag the circles that don't match
Image processing in the sensor
Eq – input image after
greyscaling
Th – after
thresholding
C1 – after contour
tracing + filling convex
hull
C2 – after dilating
Circle – enclosing
circle
Cost of sending an image
BeagleBone Black (TI Sitara AM335x)+Telit
GL865 modem, image size: 4Kbytes
Architectures:
- GL865 as a modem, all the logic (image
processing+communication) is on the Sitara
CPU – 10.755 mAh
- Image processing on the Sitara CPU,
communication logic on the GL865 – 3 mAh
Power consumption of
communication state machines
l Idle consumption of the Sitara CPU is a
problem in case of action-and-wait type
algorithms (typically communication state
machines)
l If the “wait” phase is long then the
processor could be put into a low-power
mode.
l A separate low-power CPU is justified just for
communication tasks.
Sensor
control
Network
Communication
+
App. logic
(Telit GL865)
Generic model
Same architecture for scalar and
image sensors
Soil sensor
Data acquisition:
ATxmega128u4
Network
Communication
+
App. logic
(Telit GL865)
App. Protocol #1
Camera sensor
Acquisition and
processing: TI
Sitara AM335x
Network
Communication
+
App. logic
(Telit GL865)
App. Protocol #2
Use case categorization
Use case Power consumption balance
between the processing and the
communication activities
Images taken at predetermined
moments of time and sent
No image processing, no balance
Images are taken continuously,
sent if relevant feature is found
Continuous image processing, no
balance*
Images taken at predetermined
moments and sent only if relevant
feature is found
Justified if the image processing
cycle consumes less than sending
the image
* Balance would mean that we compare with continuous image streaming which
is not possible over GPRS due to its low bandwidth.
Cost of image processing vs.
sending
Image processing
(acquiring and processing 5
images)
Sending the image
0.62 mAh 3 mAh
However:
l
Sitara consumes 156 mA in S3 state (69 secs to reach 3 mAh)
l
It takes 4.78 mAh to perform a shutdown-reboot cycle
l
No power saving possible in use case #3 due to high idle
consumption!
Takeaways
l
Low-power, low-consumption devices (e.g.
microcontrollers) are justified even if there's
a full-featured CPU in the system. Typical
use cases: sensor control, communication.
l
No magic bullet: high software engineering
productivity on embedded Linux but high
power consumption too.
l
Look for idle consumption!
l
Linux system optimized for extra-fast
shutdown-bootup cycle may work (but you
need a low-power sensor controller)
Questions?
paller.gabor@sze.hu
elo@sze.hu
24

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Energy-efficient operation of GSM-connected infrared rodent sensors

  • 1. Energy-efficient operation of GSM- connected infrared rodent sensor Gábor Paller, paller.gabor@sze.hu Gábor Élő, elo@sze.hu Széchenyi University, Győr 2016 February 19
  • 2. Precision agriculture and the agrodat.hu project
  • 3. • Precision agricultural management • Better control of production risks and costs • Information systems supporting decisions 3 Crop production
  • 4. AgroDat.hu project Main objective: Establish an agricultural knowledge centre and decision support system • based on data gathered by an innovative, complex sensor system and from international open repositories • relying on big data, cloud, and HPC technologies to support precision agriculture. Duration: 2014-2017 Budget: 2.4 Mrd HUF (appr. 8 MEUR) URL: www.agrodat.hu Consortium: Local Senso r Globa l
  • 5. • Information about environmental and vegetation processes (supplied off-line) • Sensors and data capture tools • Data processing system • Visualization • Decision support 5 Elements of the agricultural decision support system
  • 6. Sensor lineup l 2014 – soil and environmental sensors with simple scalar output – done l 2015 – camera sensors in multiple wavelengths with simple and intelligent triggers – research phase completed, field-ready implementation in progress l 2016 – making the camera sensor mobile
  • 8. 8 Proposed system architecture Sensor unit Sensor control Network Communication + App. logic (Telit GL865) Data server GPRS/HTTP POST requests WSGI HTTP server Database adapter Data visualization SMSC End user Mobile network SMS HP DSM (Dynamic SIM Management) SMPP 4.3+ Sensor management server Management user
  • 11. Camera sensors l Mission: observe plants and pests in wide frequency spectrum (visible and invisible) l Simple case: take a series of pictures and videos at given time spots and upload them to the server l More complicated: detect an event of interest and upload only if something interesting is happening
  • 12. Camera sensor development l Use case: common vole detection l Overpopulation due to mild winters l 2014 damage estimation: 500000 tons only in winter wheat
  • 13. l Night animal: cameras in different wavelength are needed (short- wavelength infrared and long- wavelength infrared are being tried) l Energy consumption: send images only if there's high chance of having animals in the picture → image processing on the sensor Advantages of the use case
  • 14. Common vole in short- wavelenght infrared Animal
  • 15. Common vole in long-wavelenght infrared Dynamic mapping to 256-level greyscale image
  • 16. Image processing in the sensor l Image thresholding – 80% static threshold l Get rid of spurious patches – contour tracing+convex hull filling l Close gaps - dilating by a kernel of 6x6 l Calculate circles of interesting objects – contour tracing+enclosing circles l Find out if the circles move – match the circles with the circles on the previous image and flag the circles that don't match
  • 17. Image processing in the sensor Eq – input image after greyscaling Th – after thresholding C1 – after contour tracing + filling convex hull C2 – after dilating Circle – enclosing circle
  • 18. Cost of sending an image BeagleBone Black (TI Sitara AM335x)+Telit GL865 modem, image size: 4Kbytes Architectures: - GL865 as a modem, all the logic (image processing+communication) is on the Sitara CPU – 10.755 mAh - Image processing on the Sitara CPU, communication logic on the GL865 – 3 mAh
  • 19. Power consumption of communication state machines l Idle consumption of the Sitara CPU is a problem in case of action-and-wait type algorithms (typically communication state machines) l If the “wait” phase is long then the processor could be put into a low-power mode. l A separate low-power CPU is justified just for communication tasks.
  • 20. Sensor control Network Communication + App. logic (Telit GL865) Generic model Same architecture for scalar and image sensors Soil sensor Data acquisition: ATxmega128u4 Network Communication + App. logic (Telit GL865) App. Protocol #1 Camera sensor Acquisition and processing: TI Sitara AM335x Network Communication + App. logic (Telit GL865) App. Protocol #2
  • 21. Use case categorization Use case Power consumption balance between the processing and the communication activities Images taken at predetermined moments of time and sent No image processing, no balance Images are taken continuously, sent if relevant feature is found Continuous image processing, no balance* Images taken at predetermined moments and sent only if relevant feature is found Justified if the image processing cycle consumes less than sending the image * Balance would mean that we compare with continuous image streaming which is not possible over GPRS due to its low bandwidth.
  • 22. Cost of image processing vs. sending Image processing (acquiring and processing 5 images) Sending the image 0.62 mAh 3 mAh However: l Sitara consumes 156 mA in S3 state (69 secs to reach 3 mAh) l It takes 4.78 mAh to perform a shutdown-reboot cycle l No power saving possible in use case #3 due to high idle consumption!
  • 23. Takeaways l Low-power, low-consumption devices (e.g. microcontrollers) are justified even if there's a full-featured CPU in the system. Typical use cases: sensor control, communication. l No magic bullet: high software engineering productivity on embedded Linux but high power consumption too. l Look for idle consumption! l Linux system optimized for extra-fast shutdown-bootup cycle may work (but you need a low-power sensor controller)