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Journals / Uludağ Üniversitesi Mühendislik Fakültesi Dergisi / 2026 / Cilt: 30 Sayı: 1

DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES

Güvenli İş Yerlerinin Sağlanması İçin Yapay Zekâ Tabanlı Bir Program Geliştirilmesi Ve Depolama Sektöründe Kayma, Tökezleme Ve Düşme Risklerinin Analizi

Bilal Murat(ÇANAKKALE ONSEKİZ MART ÜNİVERSİTESİ, LİSANSÜSTÜ EĞİTİM ENSTİTÜSÜ, İŞ GÜVENLİĞİ ANABİLİM DALI (DİSİPLİNLERARASI), İŞ SAĞLIĞI VE GÜVENLİĞİ (DR))0000-0002-1257-3039
Ali Riza Motorcu(ÇANAKKALE ONSEKİZ MART ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ)0000-0002-9129-8935
Yunus Kayır(GAZİ ÜNİVERSİTESİ, TEKNOLOJİ FAKÜLTESİ)0000-0001-6793-7103
Pages
17–34
Publication Date
2025-04-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

WaSaEx is pivotal in advancing workplace safety standards through its expert framework.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Artificial intelligence (AI), designed to enable machines to perform tasks requiring human cognition, is widely used across many fields.
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Key Findings & Data:The program uses an L-type (5x5) matrix method to assess risks based on user responses, providing risk scores and preventive measures for each factor.
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Conclusion & Impact:WaSaEx is pivotal in advancing workplace safety standards through its expert framework.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Yapay Zeka · Uzman Sistemler · İş Güvenliği

Abstract

Artificial intelligence (AI), designed to enable machines to perform tasks requiring human cognition, is widely used across many fields. Expert systems (ESs), a subset of AI, solve complex problems via expert knowledge. This study focuses on mitigating prevalent and complex slip, trip, and fall (STF) incidents by developing a program called WaSaEx, based on an AI-supported ES. WaSaEx, designed for offline use by occupational safety specialists, offers risk analysis, cost estimation, and training planning for occupational health and safety (OHS). Developed via Python and CLIPS, WaSaEx is ES-based, distinct from other OHS programs. This study introduces the WaSaEx program and evaluates its capability for risk analysis and preventive measures, specifically for reporting STF risks in storage areas. The program uses an L-type (5x5) matrix method to assess risks based on user responses, providing risk scores and preventive measures for each factor. It also systematically accounts for the interaction of risk factors that may lead to accidents. Consequently, WaSaEx offers a cost-effective, knowledge-based solution to enable swift and accurate risk analysis. This methodology delivers validated preventive measures and substantially reduces residual risks, thus fostering improved safety in storage environments. WaSaEx is pivotal in advancing workplace safety standards through its expert framework.

Özet

Yapay zekâ (AI), insan bilişi gerektiren görevleri yerine getirebilecek makineler geliştirmek için tasarlanmış olup, birçok alanda yaygın olarak kullanılmaktadır. Yapay zekânın bir alt dalı olan uzman sistemler (ESs), uzman bilgisi kullanarak karmaşık sorunları çözmektedir. Bu çalışma, yaygın ve karmaşık mekanizmalara sahip kayma, tökezleme ve düşme (STF) kazalarını azaltmayı amaçlayan, AI destekli bir ES olan WaSaEx programının geliştirilmesine odaklanmaktadır. WaSaEx, iş güvenliği uzmanları tarafından çevrimdışı olarak kullanılmak üzere tasarlanmış olup, iş sağlığı ve güvenliği (OHS) için risk analizi, maliyet hesaplama ve eğitim planlama gibi işlevler sunmaktadır. Python ve CLIPS kullanılarak geliştirilen WaSaEx, OHS alanında kullanılan diğer programlardan ES tabanlı olmasıyla ayrılmaktadır. Bu çalışma, WaSaEx programını tanıtarak, depolama alanlarındaki STF risklerini raporlama açısından risk analizi ve önleyici tedbirler konusundaki yetkinliğini değerlendirmektedir. Program, kullanıcı yanıtlarına dayalı olarak riskleri değerlendirmek için L-tipi (5x5) matris yöntemi kullanmakta, her bir faktör için risk skorları ve uygun önleyici tedbirler sunmaktadır. Ayrıca, depolama alanlarında kazalara yol açabilecek risk faktörlerinin etkileşimi sistematik olarak analize dahil edilmektedir. Sonuç olarak, WaSaEx, hızlı ve doğru risk analizi yapılmasını hedefleyen, maliyet etkin ve bilgi tabanlı bir çözüm sunmaktadır. Bu yöntem, doğrulanmış önleyici tedbirler sağlamanın yanı sıra artık riskleri önemli ölçüde azaltarak depolama ortamlarında güvenliğin artırılmasına katkıda bulunmaktadır. Uzman bir çerçeveye sahip olan WaSaEx, iş yeri güvenliği standartlarının geliştirilmesinde önemli bir rol oynamaktadır.

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Cite This Article

Murat, B., Motorcu, A. R., Kayır, Y. (2025). DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, Cilt: 30 Sayı: 1, 17–34. https://doi.org/10.17482/uumfd.1553249

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