GPS has made tracking animals a bit easier, allowing researchers to safely tag a subject and observe its whereabouts. However, frequent location reports come at a price, plagued with high energy consumption. And for long tracking sessions, researchers may have to resort to a larger battery at the detriment of the animal, according to IEEE Spectrum.
A new GPS tracker is set to fix this problem. Accurate tracking requires more GPS samples, however, that drives up the energy consumption. The new design predicts how much the animal will move, and during times when movement is minimal, GPS sampling is conserved. Thus, the device optimizes its energy budget.
The system was tested by a team of scientists at Australia’s CSIRO Ecosystem Sciences to track the movement of flying foxes (fruit bats). The animals play a vital role in the dispersal of seeds, and are also the host of a few infectious diseases, including Asia’s Nipah virus, and the Hendra virus in Australia.
“Key to understanding and managing these animals is to understand how they utilize landscapes and how they interact with other disease hosts, which requires a fine-grained understanding of their movement,” says Philipp Sommer, postdoctoral fellow at the CSIRO Distributed Sensing Systems Group, who helped build the GPS tracker.
The system employs three layers for accurate localization, all within a device that’s small enough for a flying fox to wear. “It accounts for the general movement patterns of the species being studied, and even the individual being tracked. Just as some humans are more likely to commute to and from work around 9 a.m. and 5 p.m., flying foxes have similar foraging schedules that are somewhat predictable,” IEEE Spectrum reports.
The first layer consists of offline training, which creates a population baseline using data from other animals of the same species. The second layer tracks the amount of energy consumed, harvested, and energy resources available. A software program exists at the third layer, which controls the sensors connected to the hardware platform. There’s also a scheduling algorithm that determines the best time to take a GPS sample, meaning that if there’s no movement, no sample will be taken.
How does the GPS tracker compare to other sampling approaches? Well, systems that use a fixed GPS sampling interval that’s trigged once the animal starts to move exhibit median tracking errors as high as 146.9 m. The energy-efficient method brings the median down to 21.6 m, which is much closer to the optimal offline algorithm performance, with a median tracking error of 15.8 m.
“Our evaluation results have shown that our approach can significantly increase positioning accuracy for a dynamic energy budget. This means that we are able to capture the trajectory of the animal with less errors or gaps compared to existing approaches,” Sommer says.
The research is described in the article, “Energy- and Mobility-Aware Scheduling for Perpetual Trajectory Tracking,” published in IEEE Transactions on Mobile Computing.