mlsanityData to 7 Oct 2026

Utilisation of Vision Systems and Digital Twin for Maintaining Cleanliness in Public Spaces

arXiv 2411.05964 ↗First posted 8 Nov 2024cs.CV eess.IVcited by 0

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Abstract (arXiv)

Nowadays, the increasing demand for maintaining high cleanliness standards in public spaces results in the search for innovative solutions. The deployment of CCTV systems equipped with modern cameras and software enables not only real-time monitoring of the cleanliness status but also automatic detection of impurities and optimisation of cleaning schedules. The Digital Twin technology allows for the creation of a virtual model of the space, facilitating the simulation, training, and testing of cleanliness management strategies before implementation in the real world. In this paper, we present the utilisation of advanced vision surveillance systems and the Digital Twin technology in cleanliness management, using a railway station as an example. The Digital Twin was created based on an actual 3D model in the Nvidia Omniverse Isaac Sim simulator. A litter detector, bin occupancy level detector, stain segmentation, and a human detector (including the cleaning crew) along with their movement analysis were implemented. A preliminary assessment was conducted, and potential modifications for further enhancement and future development of the system were identified.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 25 references that are in the map. First posted on arXiv 8 Nov 2024.

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5 of 25 references.

References · 5

  1. 2018Real-world Anomaly Detection in Surveillance Videoscited by 570
  2. 2022Slicing Aided Hyper Inference and Fine-tuning for Small Object Detectioncited by 101
  3. 2020TACO: Trash Annotations in Context for Litter Detectioncited by 38
  4. 2018Robotic Detection of Marine Litter Using Deep Visual Detection Modelscited by 24
  5. 2024pLitterStreet: Street Level Plastic Litter Detection and Mappingcited by 1

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