arXiv
Open Access
2025
Resource efficient data transmission on animals based on machine learning
Wilhelm Kerle-Malcharek
Karsten Klein
Martin Wikelski
Falk Schreiber
Timm A. Wild
Abstrak
Bio-loggers, electronic devices used to track animal behaviour through various sensors, have become essential in wildlife research. Despite continuous improvements in their capabilities, bio-loggers still face significant limitations in storage, processing, and data transmission due to the constraints of size and weight, which are necessary to avoid disturbing the animals. This study aims to explore how selective data transmission, guided by machine learning, can reduce the energy consumption of bio-loggers, thereby extending their operational lifespan without requiring hardware modifications.
Penulis (5)
W
Wilhelm Kerle-Malcharek
K
Karsten Klein
M
Martin Wikelski
F
Falk Schreiber
T
Timm A. Wild
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓