Research interests

• Acoustic and Data-Driven Biodiversity Monitoring
• Bird Communities, Species Classification, and Abundance Estimation
• Sensor Networks for Field-Based Environmental Monitoring
• Digital Tools for Applied Ecology and Conservation
• Interdisciplinary Research at the Interface of Computer Science and Ecology
• Simple, practical, and effective solutions - not overengineered ones

Curriculum Vitae

I am an interdisciplinary researcher working at the interface of computer science, ecology, and biodiversity monitoring. My research focuses on practical, data-driven methods for acoustic monitoring of bird communities: from (wireless) sensor networks and AI-based species classification to abundance estimation in real-world landscapes.

I currently contribute to the DBU-funded KIVO project, which develops an AI-supported workflow for bird monitoring, from field recordings to population estimation. The project aims to transfer my acoustic sensor network methods into practical use and evaluates them under real-world conditions together with partners from conservation, research, and applied monitoring.

My doctoral research investigated how acoustic sensor networks can move beyond species classification toward estimating species abundance. I combine wireless sensor networks, signal processing, AI-based classification, and ecological field data to develop monitoring approaches that are technically robust, reproducible, and useful in practice.

Beyond the technical side, I am interested in how digital tools can support ecological field research, conservation, and evidence-based decision-making in human-shaped landscapes.

Publications

2026

• L. Brüggemann
  “From Species Classification to Species Abundance using Acoustic Sensor Networks,”
  Doctoral Dissertation. 2026. https://doi.org/10.48693/936

2025

• D. Otten, A. Brundiers, L. Brüggemann, and N. Aschenbruck
  “Power-napping networks: Towards practically usable green segment routing for ISP backbones,”
  in Proc. 21st Int. Conf. Network and Service Management (CNSM), Bologna, Italy, Oct. 27–31, 2025.
• L. Brüggemann, D. Otten, F. Sachser, and N. Aschenbruck
  “Territorial acoustic species estimation using acoustic sensor networks,”
  in Proc. 22nd Int. Conf. Embedded Wireless Systems and Networks (EWSN), Leuven, Belgium, 2025 (Journal Track).
• L. Brüggemann, D. Otten, F. Sachser, and N. Aschenbruck
  “A novel approach to estimate the number of territorial birds in a network of spatially distributed acoustic recording units,”
  in Proc. European Bird Census Council (EBCC), part of “Bird Numbers 2025”, 2025.
• L. Brüggemann, F. Sachser, M. Dyczka, D. Otten, and N. Aschenbruck
  “Untangling the dawn chorus: Showcasing a classifier-deduced signal extraction method for wildlife localization in Austria,”
  in Proc. European Bird Census Council (EBCC), “Bird Numbers 2025”, 2025.
• L. Brüggemann, D. Otten, F. Sachser, and N. Aschenbruck
  “Territorial acoustic species estimation using acoustic sensor networks,”
  Ecological Informatics, vol. 91, art. no. 103281, 2025, ISSN 1574-9541. [pdf]
• L. Brüggemann, M. Dyczka, D. Otten, and N. Aschenbruck
  “A classifier-deduced signal extraction approach for time difference estimation in acoustic sensor networks,”
  Ecological Informatics, art. no. 103032, 2025, ISSN 1574-9541. [pdf]

2024

• L. Brüggemann, D. Otten, and N. Aschenbruck
  “Auf dem Weg zur vollständig automatisierten akustischen Erfassung territorialer Brutvögel – erste Ergebnisse aus einem informatikgestützten Ansatz,”
  Die Vogelwarte, vol. 62, no. 4, 2024.
• A. Tessmer, L. Brüggemann, and N. Aschenbruck
  “RBS-based time synchronization approach with autonomous acoustic sensors—A simulative proof of concept,”
  in Proc. IEEE 5th Int. Symp. Internet of Sounds (IS²), Erlangen, Germany, Sep. 30–Oct. 2, 2024.

2023

• L. Brüggemann and N. Aschenbruck
  “Theoretische Informatik in die Praxis überführt – wie Audiomoths und BirdNET beim Erfassen von Vogelabundanzen eingesetzt werden können,”
  Die Vogelwarte, vol. 61, no. 4, p. 341, 2023. [more]
• S. Thieme, D. Laniewski, L. Brüggemann, E. Lanfer, B. Schütz, and N. Aschenbruck
  “Demo: A reproducible link emulation environment for the evaluation of network-coded video streaming,”
  in Proc. 48th IEEE Conf. Local Computer Networks (LCN), Daytona Beach, FL, USA, Oct. 2–5, 2023.

2022

• L. Brüggemann and N. Aschenbruck
  “Making research on automated sound-based localization of birds more feasible, comparable, and reproducible,”
  Die Vogelwarte, vol. 60, no. 4, p. 338, 2022. [more]
• 🏆 Intevation-Förderpreis 2023 🏆 [more] 
  L. Brüggemann, B. Schütz, and N. Aschenbruck
  “TAWNS—A terrestrial acoustic and wireless network simulation framework,”
  in Proc. 15th EAI Int. Conf. Performance Evaluation Methodologies and Tools (VALUETOOLS), Ghent, Belgium, Nov. 16–18, 2022.

2021

• L. Brüggemann, B. Schütz, and N. Aschenbruck
  “Ornithology meets the IoT: Automatic bird classification, census and localization,”
  in Proc. IEEE 7th World Forum on Internet of Things (WFIoT), New Orleans, LA, USA, Jun. 14–16, 2021.
• T. Hänel, L. Brüggemann, F. Loske, and N. Aschenbruck
  “Long-term wireless sensor network deployments in industry and office scenarios,”
  in Proc. IEEE Int. Symp. a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Pisa, Italy, Jun. 7–11, 2021.

2020

• L. Brüggemann
  “Bird classification meets the Internet of Things—Designing a prototype of a wireless acoustic sensor system,”
  M.S. thesis, Osnabrück Univ., Osnabrück, Germany, Jun. 2020.

2019

• 🏆 Best Demonstration Award – IEEE LCN 2019 🏆
  B. Schütz, S. Thieme, N. Aschenbruck, L. Brüggemann, and D. Laniewski
  “Demonstration of Link ’em: An open source link emulation bridge for reproducible networking research,”
  in Proc. 44th IEEE Conf. Local Computer Networks (LCN), Osnabrück, Germany, Oct. 2019. [more]
• B. Schütz, S. Thieme, N. Aschenbruck, L. Brüggemann, A. Ditt, D. Laniewski, and D. Rieke
  “Link ’em: An open source link emulation bridge for reproducible networking research,”
  in Proc. Int. Conf. Networked Systems (NetSys), Munich, Germany, Mar. 2019. [ieeexplore] [more]

Teaching