[{"language":[{"iso":"eng"}],"_id":"6790","year":"2026","abstract":[{"text":"Manual waste monitoring is a labor-intensive process that can lead to unnecessary trips and overflowing waste bins due to fixed inspection schedules. Existing automated systems rely on static sensors installed inside each bin, which are difficult to scale and have not yet gained wider acceptance. Micro aerial vehicles (MAVs) can address this problem by carrying the necessary sensors to different locations as needed. This paper presents an MAV-based solution for automated waste bin monitoring. RGB images captured by the MAV are processed by a CNN to estimate fill levels without the need for in-bin sensors. The CNN is trained on a custom dataset of simulated waste bins and evaluated with respect to dataset performance and in a real application scenario. A mobile application enables operators to configure bin locations and monitor the process in real time. The MAV is controlled by a reinforcement learning policy and autonomously navigates to each bin location. The evaluation demonstrates that the CNN achieves reliable performance on both simulated and real images, and that the integrated system autonomously completes full inspection cycles. Overall, the proposed system offers a scalable and cost-efficient alternative for sustainable waste management.","lang":"eng"}],"status":"public","conference":{"start_date":"2026-06-15","end_date":"2026-06-18","location":"Lissabon, Portugal","name":"22nd International Conference on Intelligent Environments (IE)"},"citation":{"ieee":"A. Kirsch and J. Rexilius, “Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle,” in <i>22nd International Conference on Intelligent Environments (IE)</i>, Lissabon, Portugal, 2026.","apa":"Kirsch, A., &#38; Rexilius, J. (2026). Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle. In <i>22nd International Conference on Intelligent Environments (IE)</i>. Lissabon, Portugal. <a href=\"https://doi.org/10.1109/IE69249.2026.11539031\">https://doi.org/10.1109/IE69249.2026.11539031</a>","bibtex":"@inproceedings{Kirsch_Rexilius_2026, title={Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle}, DOI={<a href=\"https://doi.org/10.1109/IE69249.2026.11539031\">10.1109/IE69249.2026.11539031</a>}, booktitle={22nd International Conference on Intelligent Environments (IE)}, author={Kirsch, André and Rexilius, Jan}, year={2026} }","alphadin":"<span style=\"font-variant:small-caps;\">Kirsch, André</span> ; <span style=\"font-variant:small-caps;\">Rexilius, Jan</span>: Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle. 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V. (GI). Heidelberg: Springer, n.d.","short":"L. Deutsch, M. König, J. Rexilius, in: Gesellschaft für Informatik e. V. (GI) (Ed.), Progress in IS , Advances in Environmental Informatics, Springer, Heidelberg, n.d.","ama":"Deutsch L, König M, Rexilius J. An Adaptive Ant Colony System for Skip Loader Operations in Roll-on/Roll-off Logistics. In: Gesellschaft für Informatik e. V. (GI), ed. <i>Progress in IS , Advances in Environmental Informatics</i>. Heidelberg: Springer.","mla":"Deutsch, Luis, et al. “An Adaptive Ant Colony System for Skip Loader Operations in Roll-on/Roll-off Logistics.” <i>Progress in IS , Advances in Environmental Informatics</i>, edited by Gesellschaft für Informatik e. V. (GI), Springer.","ieee":"L. Deutsch, M. König, and J. Rexilius, “An Adaptive Ant Colony System for Skip Loader Operations in Roll-on/Roll-off Logistics,” in <i>Progress in IS , Advances in Environmental Informatics</i>, Potsdam.","apa":"Deutsch, L., König, M., &#38; Rexilius, J. (n.d.). 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