BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking
In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is sh...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/10/3343 |
| _version_ | 1817992502705127424 |
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| author | Niklas Duda Thorsten Nowak Markus Hartmann Michael Schadhauser Björn Cassens Peter Wägemann Muhammad Nabeel Simon Ripperger Sebastian Herbst Klaus Meyer-Wegener Frieder Mayer Falko Dressler Wolfgang Schröder-Preikschat Rüdiger Kapitza Jörg Robert Jörn Thielecke Robert Weigel Alexander Kölpin |
| author_facet | Niklas Duda Thorsten Nowak Markus Hartmann Michael Schadhauser Björn Cassens Peter Wägemann Muhammad Nabeel Simon Ripperger Sebastian Herbst Klaus Meyer-Wegener Frieder Mayer Falko Dressler Wolfgang Schröder-Preikschat Rüdiger Kapitza Jörg Robert Jörn Thielecke Robert Weigel Alexander Kölpin |
| author_sort | Niklas Duda |
| collection | DOAJ |
| description | In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible. |
| first_indexed | 2024-04-14T01:27:29Z |
| format | Article |
| id | doaj.art-ac7e28cb26534fb5b2af45e9915a44a8 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:27:29Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-ac7e28cb26534fb5b2af45e9915a44a82022-12-22T02:20:22ZengMDPI AGSensors1424-82202018-10-011810334310.3390/s18103343s18103343BATS: Adaptive Ultra Low Power Sensor Network for Animal TrackingNiklas Duda0Thorsten Nowak1Markus Hartmann2Michael Schadhauser3Björn Cassens4Peter Wägemann5Muhammad Nabeel6Simon Ripperger7Sebastian Herbst8Klaus Meyer-Wegener9Frieder Mayer10Falko Dressler11Wolfgang Schröder-Preikschat12Rüdiger Kapitza13Jörg Robert14Jörn Thielecke15Robert Weigel16Alexander Kölpin17Institute for Electronics Engineering, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyInstitute of Information Technology, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyInstitute of Information Technology, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyInstitute of Information Technology, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyInstitute of Operating Systems and Computer Networks, TU Braunschweig, 38106 Brunswick, GermanyChair of Computer Science 4—Distributed Systems and Operating Systems, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyHeinz Nixdorf Institute and Department of Computer Science, Paderborn University, 33098 Paderborn, GermanyMuseum für Naturkunde, Leibniz-Institute for Evolution and Biodiversity Science, 10115 Berlin, GermanyChair of Computer Science 6—Data Management, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyChair of Computer Science 6—Data Management, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyMuseum für Naturkunde, Leibniz-Institute for Evolution and Biodiversity Science, 10115 Berlin, GermanyHeinz Nixdorf Institute and Department of Computer Science, Paderborn University, 33098 Paderborn, GermanyChair of Computer Science 4—Distributed Systems and Operating Systems, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyInstitute of Operating Systems and Computer Networks, TU Braunschweig, 38106 Brunswick, GermanyInstitute of Information Technology, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyInstitute of Information Technology, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyInstitute for Electronics Engineering, Friedrich-Alexander University of Erlangen-Nürnberg, 91058 Erlangen, GermanyChair for Electronics and Sensor Systems, Brandenburg University of Technology, 03046 Cottbus, GermanyIn this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible.http://www.mdpi.com/1424-8220/18/10/3343wireless sensor networksanimal trackingadaptive sensor network |
| spellingShingle | Niklas Duda Thorsten Nowak Markus Hartmann Michael Schadhauser Björn Cassens Peter Wägemann Muhammad Nabeel Simon Ripperger Sebastian Herbst Klaus Meyer-Wegener Frieder Mayer Falko Dressler Wolfgang Schröder-Preikschat Rüdiger Kapitza Jörg Robert Jörn Thielecke Robert Weigel Alexander Kölpin BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking Sensors wireless sensor networks animal tracking adaptive sensor network |
| title | BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking |
| title_full | BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking |
| title_fullStr | BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking |
| title_full_unstemmed | BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking |
| title_short | BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking |
| title_sort | bats adaptive ultra low power sensor network for animal tracking |
| topic | wireless sensor networks animal tracking adaptive sensor network |
| url | http://www.mdpi.com/1424-8220/18/10/3343 |
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