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Long-term outdoor localisation with battery-powered devices remains an unsolved challenge,mainly due to the high energy consumption of GPS modules. The use of inertial sensors and short-range radio can reduce reliance on GPS to prolong the operational lifetime of tracking devices, butthey only provide coarse-grained control over GPS activity. An alternative yet promising approach is touse context-sensitive mobility models to guide scheduling and sampling decisions in localisationalgorithms. In this talk, I will present our work towards continental-scale long-term tracking of flyingfoxes, as part of the National Flying Fox Monitoring Program in Australia, using a model-drivenapproach. At the core of our approach is the multimodal GPS-enabled Camazotz sensor node platformthat has been designed at CSIRO for flying fox collars, with a cumulative weight just under 30g. The project has already deployed tens of devices on live flying foxes, which have been operating in thefield for several months. We are using the data from these devices to build mobility models andalgorithms for designing the next generation of software, as we will progressively deploy more than1000 nodes within the coming months. The progressive deployment of nodes coupled with delaytolerance, constrained resources, and incremental feature development raises interesting systemschallenges and opportunities, which I will highlight. The talk will also provide a snapshot of thecurrent data collection effort, and draw lessons from our activities in this area over the past 18 months