Smart Construction Sites: AI for Safety and Risk Management

This comprehensive article examines the transformation of construction site safety through artificial intelligence technologies. The construction industry has traditionally relied on reactive safety measures with significant limitations in coverage, monitoring consistency, and risk assessment accuracy. The article explores how AI-driven solutions, including computer vision systems, predictive analytics, wearable technology, and autonomous equipment, are addressing these shortcomings by enabling proactive safety management. Despite their proven benefits, the implementation of AI safety systems faces challenges related to data quality, integration with existing workflows, and privacy concerns. Through analysis of multiple case studies and research findings, the paper documents specific solutions to these challenges and presents compelling evidence of improved safety outcomes and economic returns from AI implementation. The findings demonstrate that properly implemented AI technologies can dramatically reduce safety incidents while providing substantial return on investment, indicating a fundamental paradigm shift in construction safety management from reactive to proactive approaches.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-06-24
DOI
https://doi.org/10.71097/ijsat.v16.i2.3578
Citations
1
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
1.54
Controls
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article

Smart Construction Sites: AI for Safety and Risk Management

Siva Praneeth Reddy Gudibandi -
1 citations
International Journal on Science and Technology
Occupational Health and Safety Research
1.54
article

Smart Construction Sites: AI for Safety and Risk Management

Siva Praneeth Reddy Gudibandi -
article en
1 citations

Abstract

This comprehensive article examines the transformation of construction site safety through artificial intelligence technologies. The construction industry has traditionally relied on reactive safety measures with significant limitations in coverage, monitoring consistency, and risk assessment accuracy. The article explores how AI-driven solutions, including computer vision systems, predictive analytics, wearable technology, and autonomous equipment, are addressing these shortcomings by enabling proactive safety management. Despite their proven benefits, the implementation of AI safety systems faces challenges related to data quality, integration with existing workflows, and privacy concerns. Through analysis of multiple case studies and research findings, the paper documents specific solutions to these challenges and presents compelling evidence of improved safety outcomes and economic returns from AI implementation. The findings demonstrate that properly implemented AI technologies can dramatically reduce safety incidents while providing substantial return on investment, indicating a fundamental paradigm shift in construction safety management from reactive to proactive approaches.

International Journal on Science and TechnologyVol. 16(2)
Openalex Percentile: Top 18%
Occupational Health and Safety Research
1.54
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