INTEGRATION OF AI IN CONSTRUCTION SITE SAFETY MANAGEMENT
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INTEGRATION OF AI IN CONSTRUCTION SITE SAFETY MANAGEMENT
Abstract
The integration of Artificial Intelligence (AI) into construction site safety management represents a transformative approach to mitigating hazards, enhancing decision-making, and promoting a proactive safety culture in the construction industry. Traditional safety management practices often rely on manual inspections, human judgment, and reactive measures, which are prone to errors and delays (Zhou et al., 2015). This study examines how AI-driven systems—such as computer vision, predictive analytics, Internet of Things (IoT) sensors, and machine learning algorithms—can enhance the identification, prediction, and prevention of workplace hazards on construction sites. Through a combination of literature review, data analysis, and system modelling, the research explores how AI technologies can process real-time data from cameras, drones, and wearable devices to detect unsafe behaviors, monitor environmental conditions, and alert workers or managers of potential risks (Zhang et al., 2021).
The findings reveal that AI integration significantly improves safety performance by enabling continuous monitoring, data-driven risk assessments, and automated incident reporting, thereby reducing accident rates and improving compliance with occupational safety standards (Fang et al., 2022). However, challenges such as high implementation costs, lack of technical expertise, and data privacy concerns remain barriers to full-scale adoption in developing regions like Nigeria. The study concludes that the integration of AI into construction site safety management holds substantial potential to revolutionize the sector by enhancing safety efficiency, reducing human error, and fostering sustainability in construction operations. Recommendations include capacity building, government policy support, and investment in digital infrastructure to facilitate AI adoption in construction safety management.
Keywords: Artificial Intelligence, Construction Safety, Risk Management, Computer Vision, Machine Learning, Predictive Analytics.
Table of Contents
Title: Integration of AI in Construction Site Safety Management
Abstract
Table of Contents
CHAPTER ONE: INTRODUCTION
1.1 Background of the Study
1.2 Statement of the Problem
1.3 Aim and Objectives of the Study
1.4 Research Questions
1.5 Significance of the Study
1.6 Scope of the Study
1.7 Limitations of the Study
1.8 Definition of Key Terms
CHAPTER TWO: REVIEW OF RELATED LITERATURE
2.1 Conceptual Framework
2.1.1 Concept of Construction Safety Management
2.1.2 Artificial Intelligence and Its Components
2.1.3 Application of AI in Construction Projects
2.1.4 AI in Safety Monitoring and Risk Prediction
2.2 Theoretical Framework
2.2.1 Technology Acceptance Model (TAM)
2.2.2 Systems Theory in Safety Management
2.3 Empirical Review
2.3.1 Global Studies on AI in Construction Safety
2.3.2 AI Integration in Developing Countries
2.4 Gaps Identified in Literature
2.5 Summary of Literature Review
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Research Design
3.2 Area of the Study
3.3 Population of the Study
3.4 Sample Size and Sampling Technique
3.5 Research Instruments
3.6 Validity and Reliability of the Instrument
3.7 Method of Data Collection
3.8 Method of Data Analysis
3.9 Ethical Considerations
CHAPTER FOUR: DATA PRESENTATION, ANALYSIS AND DISCUSSION
4.1 Data Presentation
4.2 Demographic Characteristics of Respondents
4.3 Analysis Based on Research Questions
4.4 Discussion of Findings
4.4.1 Current Safety Management Practices
4.4.2 AI Tools and Technologies Used in Construction Safety
4.4.3 Benefits and Challenges of AI Integration
4.4.4 Strategies for Effective Implementation
4.5 Summary of Findings
CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Summary of the Study
5.2 Conclusion
5.3 Recommendations
5.4 Contributions to Knowledge
5.5 Suggestions for Further Studies
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