Methods in Ecology and Evolution · 2021 · 52 citations · 60 references
ComputingComputer SystemsInformation TechnologyInternet Of ThingsMobile ComputingMobile SystemsInternet Of Things ConnectivityIot Embedded SystemsMobile Internet Of ThingsMobile SensingSensor NetworksWireless Sensor NetworksBig Data ArchitectureContinuous RecordingData RetrievalEnvironmental Data RecordingMemory SpaceMobile Data CollectionSensor-based Data CollectionWireless Data Transmission
Abstract Biologging devices are deployed on animals to collect ultra‐fine‐scale movement data that reveal subsecond patterns in locomotion or long‐term patterns in motion and space use. Often these two data types, although complementary, are rarely collected within the same study, given the limiting factors of memory space, power requirements and the need to retrieve stored data from animals. Biologging requires a revolutionary advancement in data networking to overcome these restrictions that constrain big data collection; for the continuous recording and remote download of fine‐scale movement and environmental data, from long‐term deployments and multiple individuals. Here, we adopt a strategy from the Internet of Things and develop the use of Wi‐Fi as a solution for big data biologging. Our ‘WildFi’ tag uses pre‐existing, or easy‐to‐set‐up, infrastructure in smartphones and Wi‐Fi gateways. We demonstrate the power of memory management and an embedded modular software architecture for functionality, including collective data retrieval at multiple gateways. We find that Wi‐Fi, together with smart embedded software, increases the retrieval efficiency of biologging data by orders of magnitude compared to other available systems: with a transmission speed of 230 kByte/s and range of ≤200 m that is 11 times faster than Bluetooth low energy and >3000 times faster than LoRaWAN. Case studies on a domestic dog ( Canis lupus familiaris ), aviary‐housed cockatiels ( Nymphicus hollandicus ) and free‐roaming pangolins ( Smutsia temminckii ) demonstrate the functionality of the WildFi tag for remote and robust autonomous Wi‐Fi data transmission under a range of conditions. Modularity in software and hardware allows for project‐specific tailoring beyond reconfiguring sampling parameters of a biologger, which we encourage with open‐source sharing of our architecture design. Enhanced communication between animal‐attached devices, Wi‐Fi infrastructure and smartphones, alongside smart and collaborative data retrieval, eases restrictions for big data collection in animal ecology.
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