Wild Dog Alert

Summary

Wild dogs are a major problem for many livestock producers across Australia. Often, wild dog control has necessarily been reactive and expensive, with landholders and contractors effectively forced to ‘chase’ dogs after livestock have been maimed and killed.  In chronic cases this can go on for weeks, months or even years, taking a heavy toll on enterprises, families and communities. Tracking studies show that wild dogs may be present on farms for days or weeks before losses occur.

Wild Dog Alert is a system that firmly places livestock producers and other land managers on the front foot to manage wild dogs. Combining automated recognition of camera trap images with real-time messaging, the Wild Dog Alert system notifies producers that wild dogs have been detected at a camera trap on their farm before attacks occur to enable producers to act early. This gives farmers a ‘first strike’ capability in their fight against wild dogs, so they can be proactive and put in place immediate and targeted management strategies to avoid stock losses.

Three modalities have been designed and field tested;

  1. Wild Dog Alert Node – an Australian made 360 degree camera trap with an in-built computer system to detect, process and transmit images to the cloud via satellite. This device is a world first. Where a wild dog is confirmed, an alert is transmitted.
  2. Wild Dog Alert SMS – this system uses an SMS or cellular camera trap to detect and transmit images to the Wild Dog Alert Cloud where images are processed to confirm an image of a wild dog, once confirmed an alert is transmitted to a phone or computer
  3. Wild Dog Alert BuckEye Cam – this uses a VHF camera trap system and telecommunications network to detect and transmit images to the Wild Dog Alert Cloud where images are processed to confirm an image of a wild dog, once confirmed an alert is transmitted to a phone or computer
Status

Project completed

Project Leader



Dr Paul Meek
Project Team
  • Dr Paul Meek, NSW DPI
  • Dr Guy Ballard, NSW DPI
  • Dr Peter Fleming, NSW DPI
  • Peter West, NSW DPI
  • Dr Karl Vernes, UNE
  • Dr Greg Falzon, UNE
  • Dr Ehsan K Oshtorjani, UNE
  • Dr Saleh Shahinfar, UNE
  • Dr Edmund J Sadgrove, UNE
  • Dr Robert Farrell, UNE
  • Dr Beau E Johnston, UNE
  • Mr James C. Bishop, UNE
  • Mr Joshua Stover, UNE
  • Mr Amos M Munezero, UNE
  • Mr Elrond Ka-Wai Cheung, UNE
  • Mr David Luckey, UNE
  • Mr Christopher K Lawson, UNE
  • Cameron Allan, MLA
  • Ian Evans, AWI
Project Partners

This project was led by NSW DPI and UNE and supported by funding from the Australian Government Department of Agriculture, Water and Environment Meat and Livestock Australia, and Australian Wool Innovation.

Outputs

August 2020 update:

The wild dog alert project team developed and field tested four outputs that can provide land managers with accurate real time evidence that wild dogs are present on their land. The alert system uses images gathered via remote camera traps and transmitted to the cloud for processing. The team developed the algorithms that, once trained, identify wild dogs from these images. Once detected, the system then sends an alert to the land manager advising the presence of the wild dogs and the location at which they were detected.

Several automated detection systems were developed to allow users to tailor the system to their needs and the availability, or lack of, cellular mobile services across their property.

Development and testing of these products is complete, and the core project is complete. The project has entered the commercialisation phase with the State of New South Wales acting through the Department of Primary Industries within the Department of Regional NSW being nominated as the Designated Partner to take the product forward for commercialisation. CISS and the projects Commercialisation Governance Committee will monitor the progress of the commercialisation process.

Scientific publications:

  • Falzon, G., Lawson, C., Cheung, K-W., Vernes, K., Ballard, G, Fleming P, Milne H, Mather-Zardain AT and Meek PD (2019). ClassifyMe: A Field-Scouting Software for the Identification of Wildlife in Camera Trap Images. Animals, 10(1), https://doi.org/10.3390/ani10010058
  • Meek, P., Ballard, G., Falzon, G., Williamson, J., Milne, H., Farrell, R., … Fleming,P. (2020).Camera Trapping Technology and Advances: into the New Millennium. Australian Zoologist40(3), 392-403
  • Falzon, G., Lawson, C., Cheung, K-W., Vernes, K., Ballard, G, Fleming P, Glen, A, Milne H, Mather-Zardain,AT and Meek,PD (2020). ClassifyMe: A field-scouting software for the identification of wildlife in camera trap images. Animals, 10(1),58

This project:

  1. Developed a species and individual recognition system based on camera trap imagery
  2. Tested and refined a telecommunication system suitable for remote transmission of image data and early alert messaging
  3. Constructed a standalone device with the capability to detect the presence of wild dogs, recognise them to species and individual level, and initiate transmission of an alert using satellite transmission
  4. Produced image recognition software to fast-track camera trap image processing; ClassifyMe
  5. Robustly tested all elements of the wild dog alert system.

This research project was world class and places the project team at the edge of Blue Sky Technology. The devices are currently being refined for commercialisation.

Media releases: 

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