센서 기술(Sensing technology)과 비전 기술(Vision Technology)을 이용한 건설작업자 안전관리 관련 연구 동향

  • An, Chang-Beom (The Durham School of Architectural Engineering and Construction University of Nebraska)
  • Published : 2014.04.01

Abstract

Keywords

References

  1. Amir H. Behzadan, Zeeshan Aziz, Chimay J. Anumba, Vineet R. Kamat, Ubiquitous location tracking for contextspecific information delivery on construction sites,Automation in Construction 17 (6) (2008) 737-748. https://doi.org/10.1016/j.autcon.2008.02.002
  2. Cheng, T., Migliaccio, G., Teizer, J., and Gatti, U. (2013). Data Fusion of Real-Time Location Sensing and Physiological Status Monitoring for Ergonomics Analysis of Construction Workers. Journal of Computing in Civil Engineering, 27(3), 320-335. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000222
  3. Chi, S., and Caldas, C. H. (2011). Automated Object Identification Using Optical Video Cameras on Construction Sites. Computer-Aided Civil and Infrastructure Engineering, 26(5), 368-380. https://doi.org/10.1111/j.1467-8667.2010.00690.x
  4. CPWR. (2013). The Construction Chart Book. The Center for Construction Research and Training.
  5. Escorcia, V., Davila, M., Golparvar-Fard, M., and Niebles, J. (2012). Automated Vision-Based Recognition of Construction Worker Actions for Building Interior Construction Operations Using RGBD Cameras. Construction Research Congress 2012, American Society of Civil Engineers, 879-888.
  6. Gatti, U., Migliaccio, G., and Schneider, S. (n.d.). Wearable Physiological Status Monitors for Measuring and Evaluating Workers Physical Strain: Preliminary Validation. Computing in Civil Engineering (2011), American Society of Civil Engineers, 194-201.
  7. Han, S., Lee, S., and Pena-Mora, F. (2013). Comparative Study of Motion Features for Similarity-Based Modeling and Classification of Unsafe Actions in Construction. Journal of Computing in Civil Engineering, Accepted
  8. Han, S., and Lee, S. (2013). A vision-based motion capture and recognition framework for behavior-based safety management. Automation in Construction, 35, 131-141. https://doi.org/10.1016/j.autcon.2013.05.001
  9. Houtan, J., Ahn, C. R., and Stentz, T. (2014). The Validation of Gait-Stability Metrics to Assess Construction Workers Fall Risk. Proceedings of International Conference on Computing in Civil and Building Engineering (ICCBE 2014), Orlando, FL, 23 -25 June 2014. University of Florida.
  10. Joshua, L., and Varghese, K. (2011). Accelerometer- Based Activity Recognition in Construction. Journal of Computing in Civil Engineering, 25(5), 370-379. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000097
  11. Marks, E., and Teizer, J. (2013). Evaluation of the Position and Orientation of (Semi-) Passive RFID Tags for the Potential Application in Ground Worker Proximity Detection and Alert Devices in Safer Construction Equipment Operation. Computing in Civil Engineering (2013), American Society of Civil Engineers, 645-652.
  12. NSC. (2012). Injury Facts. National Safety Council.
  13. Pradhananga, N., and Teizer, J. (2013). Automatic spatio-temporal analysis of construction site equipment operations using GPS data. Automation in Construction, 29, 107-122. https://doi.org/10.1016/j.autcon.2012.09.004
  14. Razavi, S. N., and Haas, C. T. (2010). Multisensor data fusion for on-site materials tracking in construction. Automation in Construction, 19(8), 1037 -1046. https://doi.org/10.1016/j.autcon.2010.07.017
  15. Ray, S. J., and Teizer, J. (2012). Real-time construction worker posture analysis for ergonomics training. Advanced Engineering Informatics, 26(2), 439 -455. https://doi.org/10.1016/j.aei.2012.02.011
  16. Taneja, S., Akcamete, A., Akinci, B., Garrett, J. H., East, E. W., and Soibelman, L. (2010). Analysis of three indoor localization technologies to support facility management field activities. In Proceedings of the International Conference on Computing in Civil and Building Engineering, Nottingham, UK.
  17. Torrent, D., and Caldas, C. (2009). Methodology for Automating the Identification and Localization of Construction Components on Industrial Projects. Journal of Computing in Civil Engineering, 23(1), 3 -13. https://doi.org/10.1061/(ASCE)0887-3801(2009)23:1(3)
  18. Waehrer, G. M., Dong, X. S., Miller, T., Haile, E., and Men, Y. (2007). Costs of occupational injuries in construction in the United States. Accident Analysis & Prevention, 39(6), 1258 -1266. https://doi.org/10.1016/j.aap.2007.03.012
  19. Wu, W., Yang, H., Chew, D. A. S., Yang, S., Gibb, A. G. F., and Li, Q. (2010). Towards an autonomous real-time tracking system of near-miss accidents on construction sites. Automation in Construction, 19(2), 134 -141. https://doi.org/10.1016/j.autcon.2009.11.017
  20. Yang, K., Aria, S., Ahn, C. R., and Stentz, T. (2014). Automated detection of near-miss fall incidents in iron workers using inertial measurement units. Construction Research Congress.