stakeholders) for simple approach,
understandable safety planning, and other
advanced communication purposes.
6 DISCUSSION AND
CONCLUSION
This paper proposes an innovative approach based
on the severity of fatalities, construction activities
for constructing a 4D-BIM-based RTSP to provide
adequate TSF recommenda-tion in specific spatial
and temporal simulation. The studied approach has
the potential to identify the most dangerous risk
factors among fatality causes, corresponding
prioritize providing safety prevention automatically.
The system en-ables to update the best practice
safety measures in order of importance, improve
safety management process, and finally reducing
errors in searching and using safety data. To fulfill
the objective, the various accident reports associated
with Fatal Four were analyzed and carefully
evaluated. Based on this investigation, scenario of
the unsafe conditions were identified for the purpose
of providing TSF simulation. By taking advantage of
4D-BIM, a plugin was built to allow upload and
navigate FFA data and TSF system in an intuitive
way.
Proposed system able to enhance safety
management, re-duce manager responsibility, and
simplify worker’s approach. It resulting in
impressive efficiencies in reducing risks and
accidents happening in construction. In the research,
there are multiple steps which were executed for
developing RTSP system. This works also reveals
some limitations that it is nec-essary for developing
an ideal and accurate 4D-BIM platform to
accomplish specific safety tasks and conditions
update. The aim of the assessment method is Fatal
four, the remaining factors that take part 40 percent
of construction fatality cause would explore in
further investigation. Agruablelly, the accu-rate of
RTSP concept depends on the number of fatality
cases evaluated in producing severity accident rate.
Further research would be necessary to collect more
fatalities data and scope down on fatalities rate in the
small and medium enterprises (SMEs). Besides, the
FFA-based computer vision application to remotely
monitor calculate the severity of accident occur-
rences of workers will be experimental perform.
Additionally, it would also be worthwhile to
consider the effect of utilizing Artificial intelligence
(AI) to automatically complete FFA pro-cess and
recommend accurately risk prevention. On the other
hand, we also going to integrate the system with
Augmented reality (AR) technologies to brings real
experiences method to users. The experiment
implementation will be evaluated in the real
construction site in Viet Nam and South Korea to
compare the practical application of this system in
developing and developed country.
ACKNOWLEDGEMENTS
This work was supported by the National Research
Foun-dation of Korea(NRF) grant funded by the
Korea govern-ment(MSIP). (No. NRF-
2019R1A2B5B02070721); Chung-Ang University
[research grant in 2019].
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