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Traces of flying foxes that are tracked with our Camazotz long-term tracking nodes, from all across Australia, as part of the National Flying Fox Monitoring Program

The Distributed Sensing Systems Group focuses its research on algorithms and methods that underpin large scale and long-term deployment of sensor networks to form an Internet of Things. More specifically, we address the problems of how to maximise information return from resource-constrained and distributed sensing devices. We solve these problems by applying our expertise in the following areas:

  • Distributed algorithms: that include local processing subject to resource constraints, with the possibility of cooperation among co-located nodes
  • Autonomous operation: allows our systems to adapt to new previously un-encountered contexts through adaptation and online learning
  • Sustainable computing: ensures that energy-constrained systems can match the energy input from harvesting sources is used to maximise information return while operating near-perpetually
  • Real-time classification: processes incoming sensor streams locally to transform them into meaningful classes that can be communicated over low bandwidth wireless links
  • Sensor modeling: uses the incoming sensor data to build models of the spatial and temporal dynamics of monitored processes, both to address an end user need and to feed back into optimising the operation of the system. A particular focus of this area is mobility mining: transforming large scale movement data from specialised and general platforms into meaningful movement models for prediction and optimisation


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