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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