We describe the design and implementation of Vildehaye, a family of versatile, widely-applicable, and field-proven tags for wildlife sensing and radio tracking. The family includes 6 distinct hard-ware designs for tags, 3 add-on boards, a programming adapter, and base stations; modular firmware for tags and base stations (both standalone low-power embedded base stations and base stations tethered to a computer running Linux or Windows); and desk-top software for programming and configuring tags, monitoring tags, and downloading and processing sensor data. The tags are versatile: they support multiple packet formats, data rates, and frequency bands; they can be configured for minimum mass (down to less than 1 g), making them applicable to a wide range of flying and terrestrial animals, or for inclusion of important sensors and large memories; they can transmit packets compatible with time-of-arrival transmitter-localization systems, tag identification and state packets, and they can reliably upload sensor data through their radio link. The system has been designed, upgraded, and main-tained as an academic research project, but it has been extensively used by 5 different groups of ecologists in 4 countries over a period of 5 years. More than 7100 tags have been produced and most of these have been deployed. Production used 41 manufacturing runs. The tags have been used in studies that so far resulted in 9 scientific publications in ecology (including in Science). The paper describes innovative design aspects of Vildehaye, field-use experiences, and lessons from the design, implementation, and maintenance of the system. Both the hardware and software of the system are open.
|Original language||American English|
|Title of host publication||Proceedings - 21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||14|
|State||Published - 2022|
|Event||21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022 - Virtual, Online, Italy|
Duration: 4 May 2022 → 6 May 2022
|Name||Proceedings - 21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022|
|Conference||21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022|
|Period||4/05/22 → 6/05/22|
Bibliographical noteFunding Information:
Acknowledgments. This research was supported in part by the Minerva Foundation, the Minerva Center for Movement Ecology, grants ISF-965/15 and 1919/19 from the Israel Science Foundation, a grant from the Gesellschaft für Ökologie, DFG funded research training group BioMove (RTG 2118-1), DFG project UL 546/1-1, and Dutch Research Council grant VI.Veni.192.051. Thanks to the reviewers and shepherd for comments and suggestions.
© 2022 IEEE.