Projects per year
Project Details
Description
The ASIR projects aims to develop an autonomous robot for continuous inspections of sewer pipes, for improved asset management of the sewer networks.
The ASIR project is a collaboration between Aalborg University, University of Southern Denmark, Aarhus Vand, Vandcenter Syd, HOFOR, Tiny Mobile Robots, INLOC Robotics, Envidan, and, FKSSlamson,
The ASIR project is a collaboration between Aalborg University, University of Southern Denmark, Aarhus Vand, Vandcenter Syd, HOFOR, Tiny Mobile Robots, INLOC Robotics, Envidan, and, FKSSlamson,
| Acronym | ASIR |
|---|---|
| Status | Finished |
| Effective start/end date | 01/11/2018 → 30/04/2022 |
Collaborative partners
- University of Southern Denmark
- Aarhus Vand A/S
- Vandcenter Syd A/S
- HOFOR
- Tiny Mobile Robots (lead)
- Envidan A/S
- FKSSlamson
- INLOC Robotics
Funding
- Innovation Fund Denmark: DKK13,000,000.00
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Impacts
-
Robots find defects in sewers
Moeslund, T. B. (Participant), Bahnsen, C. H. (Participant) & Haurum, J. B. (Participant)
Impact: Economic impact, Other impact
Projects
- 1 Finished
-
Value Creation in the Utility Sector Using Machine Learning
Hansen, B. D. (PI), Moeslund, T. B. (PI) & Jensen, D. G. (PI)
01/01/2019 → 31/12/2021
Project: Research
-
Multi-scale hybrid vision transformer and Sinkhorn tokenizer for sewer defect classification
Haurum, J. B., Madadi, M., Guerrero, S. E. & Moeslund, T. B., Dec 2022, In: Automation in Construction. 144, 104614.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile31 Citations (Scopus)472 Downloads (Pure) -
Multi-Task Classification of Sewer Pipe Defects and Properties using a Cross-Task Graph Neural Network Decoder
Haurum, J. B., Madadi, M., Guerrero, S. E. & Moeslund, T. B., 2022, Proceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022. IEEE (Institute of Electrical and Electronics Engineers), p. 1441-1452 12 p. (IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)).Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
Open Access11 Citations (Scopus) -
3D Sensors for Sewer Inspection: A Quantitative Review and Analysis
Bahnsen, C. H., Johansen, A. S., Philipsen, M. P., Henriksen, J. W., Nasrollahi, K. & Moeslund, T. B., 6 Apr 2021, In: Sensors. 21, 7, 27 p., 2553.Research output: Contribution to journal › Review article › peer-review
Open AccessFile38 Citations (Scopus)393 Downloads (Pure)
Press/Media
-
FORSKER I SPILDEVAND: Kontinuerlig inspektion af kloakrør kan spare forsyninger for et trecifret millionbeløb – om året
15/05/2022
1 item of Media coverage
Press/Media: Press / Media
-
Tv-inspektioner af kloakker kan automatiseres
15/03/2022
1 Media contribution
Press/Media: Press / Media
-
Data og algoritmer skal hjælpe med at vedligeholde vores kloakker
Haurum, J. B. & Moeslund, T. B.
21/06/2021
1 Media contribution
Press/Media: Press / Media
Datasets
-
Sewer-ML
Haurum, J. B. (Creator) & Moeslund, T. B. (Creator), sciencedata.dk, 18 Jun 2021
https://forms.gle/hBaPtoweZumZAi4u9 and one more link, https://vap.aau.dk/sewer-ml/ (show fewer)
Dataset
-
AAU Sewer Defect Point Cloud Dataset
Haurum, J. B. (Creator), Allahham, M. M. J. (Creator), Lynge, M. S. (Creator), Henriksen, K. S. (Creator), Nikolov, I. A. (Creator) & Moeslund, T. B. (Creator), Kaggle, 2021
https://www.kaggle.com/aalborguniversity/sewerpointclouds
Dataset