Researchers at Murdoch University’s Harry Butler Institute have partnered with a global technology leader to deliver novel ways to monitor the environment in remote locations. The monitoring technique provides a wireless solution to observe environmental conditions in areas that lack reliable networks and could pave the way for remote detection of bushfires and other potentially damaging scenarios.
The Harry Butler Institute Business Manager stated that said many remote locations in Western Australia and beyond lacked 3G and 4G internet coverage, posing a challenge for suitable communication solutions. The team has been investigating a cost-effective wireless IoT [Internet of Things] solution known as LoRaWAN, that offers low power, long range, wide area network data sensor technology. The network also succeeds alternatives such as WiFi and Bluetooth, as it doesn’t require cellular network coverage, making it ideal to reach remote areas including national parks.
A pilot program had already successfully moved data between Murdoch University’s South Street campus and the city. Two of the team’s researchers were able to move environmental data such as temperature, soil moisture and air quality data, but also demonstrated further innovation by moving images over LoRaWAN – something this network wasn’t even built for.
This innovative and efficient technology solution could provide researchers and emergency personnel the ability to monitor remote locations from anywhere, at any time. Senior Lecturer David Murray said the pilot has given researchers the confidence to pursue further technological developments to assist in the early detection of smoke and fire.
The team is now determining how cost-effective cameras can be developed to monitor bushfires using artificial intelligence models to identify the risk of smoke and fire, and by sending alerts via a LoRaWAN network, he said.
It was noted that this approach, in addition to weather sensors and low-resolution images that can be sent over the network for manual validation, could alert emergency workers to fire threats much earlier.
The network could also be deployed in other diverse scenarios including animal monitoring, with testing previously conducted at Murdoch to monitor the presence of quenda populations at its South Street campus.
The Pro Vice Chancellor of the Harry Butler Institute stated that the low-cost technology option was an exciting prospect for the future of environmental surveillance. This real-time technology could pave the way for monitoring networks not only in Western Australia but globally, he said.
LoRaWAN provides the option of overcoming limitations, saving time, money and resources and its potential environmental applications, including supporting emergency bushfire personnel and researchers monitoring vulnerable species such as quenda, will be significant.
The project further enhances the partnership between Murdoch University and the global tech leader and strengthens both organisations’ commitment to developing technology that can aid the environment and safeguard the sustainability of the planet.
Australia’s bushfire season currently lasts for 130 days a year, lengthened by almost a month in the past four decades, according to new research. Recent wildfire outbreaks across the globe have sparked concern that climate change is increasing fire incidence, threatening human livelihood and biodiversity, and perpetuating climate change.
Various climate models highlight that the prevalence and extremity of fire weather have already emerged beyond its pre-industrial variability in the Mediterranean as a result of climate change, and emergence will become increasingly widespread at additional levels of warming. Moreover, several of the major wildfires experienced in recent years, including the Australian bushfires of 2019/2020, have occurred amidst fire weather conditions that were considerably more likely due to climate change. The report notes that advances in the observation of fire and understanding of its controlling factors support the addition or optimisation of a variety of processes in models.