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Energy-efficient Mobile Sensor Data Offloading via WiFi using LoRa-based Connectivity Estimations

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Gesellschaft für Informatik, Bonn


Animal monitoring in natural habitats provides significant insights into the animals’ behavior, interactions, health, or external influences. However, the sizes of monitoring devices attachable to animals strongly depends on the animals’ sizes, and thus the range of possible sensors including batteries is severely limited. Gathered data can be offloaded from monitoring devices to data sinks in a wireless sensor network using available radio access technologies, but this process also needs to be as energy-efficient as possible. This paper presents an approach to combine the benefits of high-throughput WiFi and robust low-power LoRa communication for energy-efficient data offloading. WiFi is only used when connectivity between mobile devices and data sinks is available, which is determined by LoRa-based distance estimations without the need for additional GPS sensors. A prototypical implementation on low-end commodity-off-the-shelf hardware is used to evaluate the proposed approach in a German mixed forest using a simple path loss model for distance estimation. The system provides an offloading success rate of 87%, which is similar to that of a GPS-based approach, but with around 37% less power consumption.


Zobel, Julian; Frommelt, Paul; Lieser, Patrick; Höchst, Jonas; Lampe, Patrick; Freisleben, Bernd; Steinmetz, Ralf (2021): Energy-efficient Mobile Sensor Data Offloading via WiFi using LoRa-based Connectivity Estimations. INFORMATIK 2021. DOI: 10.18420/informatik2021-037. Gesellschaft für Informatik, Bonn. PISSN: 1617-5468. ISBN: 978-3-88579-708-1. pp. 461-479. Workshop: Computer Science for Biodiversity (CS4BIODiversity). Berlin. 27. September - 1. Oktober 2021