Real-Time Safety Risk Identification Model during Metro Construction Adjacent to Buildings

2019 ◽  
Vol 145 (6) ◽  
pp. 04019034
Author(s):  
Sherong Zhang ◽  
Chao Shang ◽  
Chao Wang ◽  
Ran Song ◽  
Xiaohua Wang
Keyword(s):  
Real Time ◽  
Risk Identification ◽  
Safety Risk ◽  
Identification Model

scholarly journals Real-Time Safety Risk Assessment Based on a Real-Time Location System for Hydropower Construction Sites

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Hanchen Jiang ◽  
Peng Lin ◽  
Qixiang Fan ◽  
Maoshan Qiang
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Simulation Analysis ◽  
Probability Distributions ◽  
Risk Identification ◽  
Worker Safety ◽  
Safety Risk ◽  
Location System ◽  
Quantitative Calculation ◽  
Real Time Location System

The concern for workers’ safety in construction industry is reflected in many studies focusing on static safety risk identification and assessment. However, studies on real-time safety risk assessment aimed at reducing uncertainty and supporting quick response are rare. A method for real-time safety risk assessment (RTSRA) to implement a dynamic evaluation of worker safety states on construction site has been proposed in this paper. The method provides construction managers who are in charge of safety with more abundant information to reduce the uncertainty of the site. A quantitative calculation formula, integrating the influence of static and dynamic hazards and that of safety supervisors, is established to link the safety risk of workers with the locations of on-site assets. By employing the hidden Markov model (HMM), the RTSRA provides a mechanism for processing location data provided by the real-time location system (RTLS) and analyzing the probability distributions of different states in terms of false positives and negatives. Simulation analysis demonstrated the logic of the proposed method and how it works. Application case shows that the proposed RTSRA is both feasible and effective in managing construction project safety concerns.

scholarly journals The place of artificial intelligence in the risk management process

2021 ◽  
Vol 120 ◽  
pp. 02013
Author(s):  
Petya Biolcheva
Keyword(s):  
Artificial Intelligence ◽  
Risk Assessment ◽  
Risk Management ◽  
Real Time ◽  
Risk Identification ◽  
Management Process ◽  
Whole Process ◽  
Risk Management Process ◽  
Problematic Issue ◽  
The Individual

In recent years, there has been increasing talk of the rapid entry of artificial intelligence into risk management. All the benefits it would bring over the whole process are often commented on: real-time results, processing large amounts of data, more complete risk identification, more accurate risk assessment, etc. There are also negative moods that make various experts feel threatened by their need to be replaced by artificial intelligence. Another problematic issue that arises is related to the transparency of algorithms and the increase in cyber risks [6]. This material aims to identify the individual elements at the stages of risk management in which artificial intelligence (AI) can and should be applied alone, in combination with expert opinion or not. Here it is shown that because of the use of AI the efficiency of the whole process is significantly increased, first of all by conducting in-depth analyses, and the decisions are made by the risk management experts. This proves its usefulness and increases the confidence of experts in it.

scholarly journals Novel strategy for food safety risk management and communication: Risk identification for benzoic acid residues in pickled vegetables

2020 ◽  
Vol 8 (10) ◽  
pp. 5419-5425
Author(s):  
Ding‐Yan Lin ◽  
Cheng‐Han Tsai ◽  
Ying Huang ◽  
Siou‐Bang Ye ◽  
Che‐Hsuan Lin ◽  
...  
Keyword(s):  
Risk Management ◽  
Food Safety ◽  
Benzoic Acid ◽  
Risk Identification ◽  
Safety Risk ◽  
Novel Strategy ◽  
Food Safety Risk ◽  
Pickled Vegetables

Safety risk identification system for metro construction on the basis of construction drawings

2012 ◽  
Vol 27 ◽  
pp. 120-137 ◽  
Author(s):  
L.Y. Ding ◽  
H.L. Yu ◽  
Heng Li ◽  
C. Zhou ◽  
X.G. Wu ◽  
...  
Keyword(s):  
Risk Identification ◽  
Identification System ◽  
Safety Risk
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