Research On Intelligent Behavioral Safety Management Framework For Construction Workers Based On Field Theory

The construction industry is a high hazard industry.For years,construction has led all industries in the total number of worker deaths,most of which are caused by unsafe behaviors of workers.Behavior-Based Safety(BBS)has always been an important research topic to reduce accidents and facilitate safety management.On the basis of the traditional BBS program,this study has introduced artificial intelligence technology and psychological field theory to support the root cause analysis and automatic observation and management for workers' unsafe behavior.The research contents of this study are as follows:(1)An unsafe behavior formation mechanism for construction workers.According to the relevant concepts of field theory,a behavioral safety mechanism analysis model of construction workers is proposed.This dissertation has illustrated the connotation and influences of psychological space and motivating forces on workers' behaviors.It is also pointed out that the vector sum of the motivating forces of the psychological field and the self-control of personality traits ultimately determines whether unsafe behaviors occur or not.It provides a basis for the following analysis and classified management of self-control personality traits.(2)Intelligent detection method for construction workers' unsafe behaviors.Considering the great differences of construction behavior specifications in different scenarios,this dissertation proposes a scenario based intelligent detection method for construction workers' unsafe behaviors.Firstly,the construction scenarios are defined and detected according to the locations and space division of central objects.Then,the calling and combination mechanisms of the vision-based subprogram modules are established to solve the automatic recognition task for construction workers' unsafe behaviors.(3)A classified management system for construction workers' unsafe behaviors.According to the behavior intervention theory,a safety performance evaluation system and a "4I" based classified management system are designed for workers with different selfcontrol personality traits.It aims to motivate the workers to work in a safe manner,help them with sufficient support,and finally reshape and improve workers' behavioral safety habits.In the design of the personalized behavioral safety management system,full consideration is given to the personal characteristics of their self-control traits,and specific management measures are formulated accordingly to achieve personalized correction of unsafe behaviors of workers.(4)Case study.An intelligent identification and classification management system for behavior safety which is used to automatically collect and obtain workers' behavior safety data was developed.Then,a comparative experiment was carried out on three construction sites.It had been verified whether there is a significant difference between the experimental group and the control group in reducing the rate of unsafe behaviors.The performance of the classified management system was analyzed by comparing the changes of workers' selfcontrol level before and after adopting classified management strategies.In this study,psychological field theory and artificial intelligence technology are applied to behavior-based safety management of construction workers.Root causes and paths of unsafe behaviors are discussed.Unsafe behavior records and psychological field parameters are obtained to mine behavior patterns of workers.Classified management strategies are adopted to help reduce unsafe behaviors of workers.