Deliverables

Assignments

We distinguish between unmarked and marked deliverables (“Studien- und Prüfungsleistung”). Both are required for passing the course but only the latter are marked.

Your unmarked assignment will be to present a paper on recent developments in the world of proximity sensing in the form of a 12 minute presentation followed by a 3 minute discussion. Everybody is requested to prepare 3 questions for the topic of each of your peers.

Topics of the seminar

1) Holzbauer et al. (2025, preprint).Do camera light traps provide similar data as conventional funnel light traps? DOI 2) Drake et al. (2024) Monitoring insect numbers and biodiversity with a vertical-beam entomological radar DOI 3) Chiavassa et al. (2024) The Field Automatic Insect Recognition-Device—A Non-Lethal Semi-Automatic Malaise Trap for Insect Biodiversity Monitoring: Proof of Concept DOI 4) Alberti et al. (2023) Bioacoustic IoT Sensors as Next-Generation Tools for Monitoring: Counting Flying Insects through Buzz DOI 5) Calvus et al (2025) In-field monitoring of ground-nesting insect aggregations using a scaleable multi-camera system DOI 6) Jiang et al (2022) Acoustic detection of the wood borer, Semanotus bifasciatus, as an early monitoring technology DOI 7) Alcocer, et al. (2022). Acoustic indices as proxies for biodiversity: a meta-analysis. Biological Reviews 97, 2209–2236. DOI 8) Naqvi et al. (2022) Camera traps are an effective tool for monitoring insect–plant interactions DOI 9) Suto (2022) A Novel Plug-in Board for Remote Insect Monitoring DOI 10) Sittinger et al. (2024) Insect detect: An open-source DIY camera trap for automated insect monitoring DOI 11) Feng (2025) First high-resolution vertical-looking radar for long-term automatic observation of high-flying insects in Asia DOI 12) Ratnayake (2023) Spatial Monitoring and Insect Behavioural Analysis Using Computer Vision for Precision Pollination DOI 13) Bjerge et al. (2021) Real-time insect tracking and monitoring with computer vision and deep learning DOI 14) Rydhmer et al. (2022) Automating insect monitoring using unsupervised near-infrared sensors DOI 15) Saha et al. (2024) Monitoring Mosquito Abundance: Comparing an Optical Sensor with a Trapping Method DOI 16) Wallace et al. (2023) Camera-based automated monitoring of flying insects in the wild (Camfi). II. flight behaviour and long-term population monitoring of migratory Bogong moths in Alpine Australia DOI

Project work

Your marked assignment will be to prepare a report consisting of an introduction, a methods part, an analysis, description of results, and discussion. Additionally, there should be a a description of the setting, which should be presented in a way that is easy to understand for non-experts and allows for easy replication. This assignment can also be presented in form of a github page. You can submit group projects with up to 3 people, but each person must individually produce at least 1.5 page of text and a graph and mark it accordingly.

Master students must additionally submit 2 pages of substantial suggestions for further development.