---
_id: '6790'
abstract:
- lang: eng
  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.
author:
- first_name: André
  full_name: Kirsch, André
  id: '229807'
  last_name: Kirsch
- first_name: Jan
  full_name: Rexilius, Jan
  id: '245736'
  last_name: Rexilius
  orcid: 0000-0002-4579-214X
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0002-4579-214X/work/208820721
citation:
  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. In: <i>22nd International Conference on Intelligent Environments
    (IE)</i>, 2026'
  ama: 'Kirsch A, Rexilius J. Vision-Based Autonomous Waste Bin Fill-Level Monitoring
    with a Micro Aerial Vehicle. In: <i>22nd International Conference on Intelligent
    Environments (IE)</i>. ; 2026. doi:<a href="https://doi.org/10.1109/IE69249.2026.11539031">10.1109/IE69249.2026.11539031</a>'
  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} }'
  chicago: Kirsch, André, and Jan Rexilius. “Vision-Based Autonomous Waste Bin Fill-Level
    Monitoring with a Micro Aerial Vehicle.” In <i>22nd International Conference on
    Intelligent Environments (IE)</i>, 2026. <a href="https://doi.org/10.1109/IE69249.2026.11539031">https://doi.org/10.1109/IE69249.2026.11539031</a>.
  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.
  mla: Kirsch, André, and Jan Rexilius. “Vision-Based Autonomous Waste Bin Fill-Level
    Monitoring with a Micro Aerial Vehicle.” <i>22nd International Conference on Intelligent
    Environments (IE)</i>, 2026, doi:<a href="https://doi.org/10.1109/IE69249.2026.11539031">10.1109/IE69249.2026.11539031</a>.
  short: 'A. Kirsch, J. Rexilius, in: 22nd International Conference on Intelligent
    Environments (IE), 2026.'
conference:
  end_date: 2026-06-18
  location: Lissabon, Portugal
  name: 22nd International Conference on Intelligent Environments (IE)
  start_date: 2026-06-15
date_created: 2026-03-06T12:30:43Z
date_updated: 2026-06-16T10:10:34Z
department:
- _id: '102'
doi: 10.1109/IE69249.2026.11539031
keyword:
- Waste monitoring
- Waste level estimation
- MAV navigation
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/document/11539031
project:
- _id: A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D
  name: Institute for Building Intelligence
publication: 22nd International Conference on Intelligent Environments (IE)
publication_status: published
quality_controlled: '1'
related_material:
  record:
  - id: '6993'
    relation: other
    status: submitted
status: public
title: Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial
  Vehicle
type: conference
user_id: '229807'
year: '2026'
...