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

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.
51. Jahrestagung der Gesellschaft für Informatik (INFORMATIK 2021). virtual conference (27.09.-01.10.2021)
doi: 10.18420/informatik2021-037
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

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.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2021
Autor(en): Zobel, Julian ; Frommelt, Paul ; Lieser, Patrick ; Höchst, Jonas ; Lampe, Patrick ; Freisleben, Bernd ; Steinmetz, Ralf
Art des Eintrags: Bibliographie
Titel: Energy-efficient Mobile Sensor Data Offloading via WiFi using LoRa-based Connectivity Estimations
Sprache: Englisch
Publikationsjahr: 27 Oktober 2021
Verlag: Gesellschaft für Informatik e.V.
Buchtitel: INFORMATIK 2021: Computer Science & Sustainability
Reihe: GI-Edition: Lecture Notes in Informatics
Band einer Reihe: P314
Veranstaltungstitel: 51. Jahrestagung der Gesellschaft für Informatik (INFORMATIK 2021)
Veranstaltungsort: virtual conference
Veranstaltungsdatum: 27.09.-01.10.2021
DOI: 10.18420/informatik2021-037
Kurzbeschreibung (Abstract):

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.

Freie Schlagworte: emergenCITY_KOM, emergenCITY
Zusätzliche Informationen:

Workshop Computer Science for Biodiversity (CS4BIODiversity)

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Multimedia Kommunikation
DFG-Sonderforschungsbereiche (inkl. Transregio)
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet
Hinterlegungsdatum: 28 Mär 2023 13:04
Letzte Änderung: 23 Jan 2024 08:38
PPN: 509496601
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