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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.18938 |
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| _version_ | 1866915357329981440 |
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| author | Wang, Yanke Ng, Yu Hin Liang, Haobo Chang, Ching-Wei Chen, Hao |
| author_facet | Wang, Yanke Ng, Yu Hin Liang, Haobo Chang, Ching-Wei Chen, Hao |
| contents | The tower crane is involving more automated and intelligent operation procedure, and importantly, the application of automation technologies to the safety issues is imperative ahead of the utilization of any other advances. Among diverse risk management tasks on site, it is essential to protect the human workers on the workspace between the tower crane and constructed building top area (construction top) from the bird's-eye view, especially with Modular Integrated Construction (MiC) lifted. Also, the camera and Light Detection And Ranging (LiDAR) can capture abundant 3D information on site, which is however yet made the best use. Considering the safety protection for humans and tower cranes, we present an AI-based fully automated safety monitoring system for tower crane lifting from the bird's-eye view, surveilling to shield the human workers on the construction top and avoid cranes' collision by alarming the crane operator. The system achieved a 3D data fusion for localization of humans and MiCs by integrating the captured information from camera and LiDAR. The state-of-the-art methods were explored and implemented into our proposed software pipeline coupled with the hardware and display systems. Furthermore, we conducted an analysis of the components in the pipeline to verify the accuracy and effectiveness of the involved methods. The display and visualization on the real site proved that our system can serve as a valuable safety monitoring toolkit on site. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_18938 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Bird's-eye view safety monitoring for the construction top under the tower crane Wang, Yanke Ng, Yu Hin Liang, Haobo Chang, Ching-Wei Chen, Hao Computer Vision and Pattern Recognition Systems and Control The tower crane is involving more automated and intelligent operation procedure, and importantly, the application of automation technologies to the safety issues is imperative ahead of the utilization of any other advances. Among diverse risk management tasks on site, it is essential to protect the human workers on the workspace between the tower crane and constructed building top area (construction top) from the bird's-eye view, especially with Modular Integrated Construction (MiC) lifted. Also, the camera and Light Detection And Ranging (LiDAR) can capture abundant 3D information on site, which is however yet made the best use. Considering the safety protection for humans and tower cranes, we present an AI-based fully automated safety monitoring system for tower crane lifting from the bird's-eye view, surveilling to shield the human workers on the construction top and avoid cranes' collision by alarming the crane operator. The system achieved a 3D data fusion for localization of humans and MiCs by integrating the captured information from camera and LiDAR. The state-of-the-art methods were explored and implemented into our proposed software pipeline coupled with the hardware and display systems. Furthermore, we conducted an analysis of the components in the pipeline to verify the accuracy and effectiveness of the involved methods. The display and visualization on the real site proved that our system can serve as a valuable safety monitoring toolkit on site. |
| title | Bird's-eye view safety monitoring for the construction top under the tower crane |
| topic | Computer Vision and Pattern Recognition Systems and Control |
| url | https://arxiv.org/abs/2506.18938 |