Using sensor technology to track herds of feral pigs, cattle and buffalo is key to developing more effective controls for these feral populations and protecting the environment. This innovative technology offers Indigenous land managers in remote northern Australia new ways to monitor and manage their country.
Cost-effective management of feral animals
There are large populations of feral pigs, buffalo and cattle roaming freely across vast, inaccessible areas of the Top End, destroying natural environments, undermining agricultural productivity and spreading diseases. The use of traditional control methods in northern Australia requires massive investments of time and money. A more strategic approach to feral animal control could maximise the environmental benefits gained while minimising economic costs.
Previous research on feral pigs suggests that access to food, water and shade are the key landscape elements that determine where pigs will be. The availability and distribution of each of these elements, individually and in combination, work together to determine how many animals can be supported by the landscape.
The key challenge is to understand the quality and location of these key resources and identify out how large feral mammals use these elements as the seasons change.
Understanding where animals will be at different points of the year and what resources are available to them, will help in designing better control strategies that meet local objectives.
Putting the latest technology to work in remote Australia
CSIRO and James Cook University (JCU) are collaborating with three Indigenous land management organisations – Aak Puul Ngangtam (APN) and Kalan Enterprises in Cape York Peninsula, Queensland, and Djelk Land and Sea Rangers in Arnhem Land, Northern Territory – to develop low-cost tracking devices and an environmental sensor network using the Internet of Things (IoT).
GPS tags developed in-house by Data61 and low-power, long-range wireless networks, are able to provide near real-time tracking of feral animals and monitoring of the environmental conditions they're utilising; improving data collection for remote monitoring without the cost of satellite communications.
Using big data analytical techniques and insights into each species behaviour, CSIRO will integrate these continuous data streams into a near real-time pest species tracking and monitoring system.
Feral animals join the Internet of Things
The CSIRO team has worked with the Indigenous land management groups and JCU to install the technology for the trial phase of the project, during which it will be put to the test in extreme northern Australian conditions. To date, three IoT base stations, 20 small inexpensive environmental sensors (measuring temperature, humidity, pressure and light), three high-end weather stations and 10 GPS tracking nodes have been installed at locations in Cape York and Arnhem Land. As at October 2018, data was being collected from 22 buffaloes that had been tagged in Arnhem Land and 20 pigs on Cape York.
CSIRO is using the data to develop analytical methods for near real-time modelling outputs. The environmental sensors have been placed in a gradient of vegetation types to provide data on the difference in temperature and humidity in different habitat types. An initial spatial model has integrated the data (which is being uploaded to the CSIRO Senaps cloud service every 15 minutes) into a very fine resolution model of temperature and humidity for the study area.
For example, pigs, buffalo and cattle can only tolerate a certain amount of heat before seeking out shade. Understanding how temperature and humidity changes with different habitat types will allow the team to develop very fine resolution models that can predict how much of the landscape is suitable for feral pigs, buffalo and cattle in near real-time. These models will help land managers to plan their control activities to periods and areas where they will be most effective.
Following the trial phase, there will be a large scale deployment of over 400 sensors in 2018 and 2019.