Network-based localisation and animal tracking using SigFox IoT data

Theme:

Signal Processing/Localization

Application:

Animal tracking

Contact Person:

 Anastasia Lavrenko

External collabolator:

Max Planck Institute of Animal Behavior.

Intorduction:

Low-Power Wide-Area Networks (LPWANs) such as SigFox are increasingly used for tracking small animals (e.g. bats and birds) where GPS is too heavy or too power-hungry. These systems use network-based localisation, exploiting which base stations receive a transmission and with what signal strength. In practice, this localisation is often coarse and treated as a “black box” by the network provider. However, large amounts of raw reception metadata (e.g. RSSI, station IDs, repetition patterns) are available and largely under-exploited.

Description:

Can we track small flying animals without GPS? In this project, we explore how SigFox reception metadata can be used to reconstruct animal movement trajectories, assess localisation uncertainty, and investigate how tracking performance can be improved using signal-processing and modelling techniques. The project uses real tracking data from wildlife studies and addresses a concrete, interdisciplinary problem at the interface of wireless communication, signal processing, and ecological monitoring.

You will learn:

• How real-world IoT and LPWAN systems operate
• Limitations of RSSI-based localisation
•  Practical data analysis with imperfect, noisy measurements
• Translating theoretical signal-processing ideas into applied solutions
• Working with real data from active research projects

Multiple Bachelor and Master projects are available on this topic.

Requirements:

You are a motivated student looking for a project topic in the field signal processing. You have interest in wireless communication and data analysis and curiosity for interdisciplinary applications. You have skills in MATLAB or Python, basic signal processing, statistics or probabilistic modelling.

Additional Info