Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers
The construction industry is considered one of the most hazardous industries. The accidents associated with construction equipment are a leading cause of fatalities in the U.S., with one-quarter of all fatalities in the construction industry due to equipment-related incidents, including collisions,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/15/1/110 |
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| author | Ren-Jye Dzeng Binghui Fan Tian-Lin Hsieh |
| author_facet | Ren-Jye Dzeng Binghui Fan Tian-Lin Hsieh |
| author_sort | Ren-Jye Dzeng |
| collection | DOAJ |
| description | The construction industry is considered one of the most hazardous industries. The accidents associated with construction equipment are a leading cause of fatalities in the U.S., with one-quarter of all fatalities in the construction industry due to equipment-related incidents, including collisions, struck-by events, and rollovers. While close collaboration among multiple equipment and humans is common, conventional collision alert mechanisms for equipment usually rely on distance sensors with static thresholds, often resulting in too many false alarms, causing drivers’ ignorance. Considering the collaborative operation scenario, this research proposes and develops a dynamic-threshold alert system by recognizing hazardous events based on the types of nearby objects with their orientation or postures and their distances to the system carrier equipment based on image-based recognition and Sim2Real techniques. Two experiments were conducted, and the results show that the system successfully reduced a large number of false near-collision alarms for the collaboration scenarios. Although the accuracy of object recognition and image-based distance estimation is feasible for practical use, it is also easily degraded in the self-obstruction scenario or for equipment with large and movable parts due to incorrect recognition of the bounding boxes of the target objects. |
| format | Article |
| id | doaj-art-499bf7ad37ef424796837f71d6d58b36 |
| institution | Kabale University |
| issn | 2075-5309 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj-art-499bf7ad37ef424796837f71d6d58b362025-01-10T13:16:04ZengMDPI AGBuildings2075-53092024-12-0115111010.3390/buildings15010110Dynamic Collision Alert System for Collaboration of Construction Equipment and WorkersRen-Jye Dzeng0Binghui Fan1Tian-Lin Hsieh2Department of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanCollege of Civil Engineering, Fuzhou University, Fuzhou 350108, ChinaDepartment of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, TaiwanThe construction industry is considered one of the most hazardous industries. The accidents associated with construction equipment are a leading cause of fatalities in the U.S., with one-quarter of all fatalities in the construction industry due to equipment-related incidents, including collisions, struck-by events, and rollovers. While close collaboration among multiple equipment and humans is common, conventional collision alert mechanisms for equipment usually rely on distance sensors with static thresholds, often resulting in too many false alarms, causing drivers’ ignorance. Considering the collaborative operation scenario, this research proposes and develops a dynamic-threshold alert system by recognizing hazardous events based on the types of nearby objects with their orientation or postures and their distances to the system carrier equipment based on image-based recognition and Sim2Real techniques. Two experiments were conducted, and the results show that the system successfully reduced a large number of false near-collision alarms for the collaboration scenarios. Although the accuracy of object recognition and image-based distance estimation is feasible for practical use, it is also easily degraded in the self-obstruction scenario or for equipment with large and movable parts due to incorrect recognition of the bounding boxes of the target objects.https://www.mdpi.com/2075-5309/15/1/110equipment collisionYOLOimage recognitionSim2Real |
| spellingShingle | Ren-Jye Dzeng Binghui Fan Tian-Lin Hsieh Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers Buildings equipment collision YOLO image recognition Sim2Real |
| title | Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers |
| title_full | Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers |
| title_fullStr | Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers |
| title_full_unstemmed | Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers |
| title_short | Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers |
| title_sort | dynamic collision alert system for collaboration of construction equipment and workers |
| topic | equipment collision YOLO image recognition Sim2Real |
| url | https://www.mdpi.com/2075-5309/15/1/110 |
| work_keys_str_mv | AT renjyedzeng dynamiccollisionalertsystemforcollaborationofconstructionequipmentandworkers AT binghuifan dynamiccollisionalertsystemforcollaborationofconstructionequipmentandworkers AT tianlinhsieh dynamiccollisionalertsystemforcollaborationofconstructionequipmentandworkers |