EMOTIONALLY INTELLIGENT CONSTRUCTION SAFETY MONITORING VIA INTEGRATION OF MACHINE LEARNING AND EXPERT-INFORMED ELECTROENCEPHALOGRAM-RELATED FEATURES

Creative Commons License

Mostofi F., Rouhikia M., Tokdemir O. B., TOĞAN V., Adeli H.

Journal of Civil Engineering and Management, cilt.32, sa.6, ss.769-784, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 6
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3846/jcem.2026.27817
  • Dergi Adı: Journal of Civil Engineering and Management
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Central & Eastern European Academic Source (CEEAS), Compendex, ICONDA Bibliographic, Directory of Open Access Journals, The International Construction Database (ICONDA), Academic Search Ultimate (EBSCO), Engineering Source (EBSCO), Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
  • Sayfa Sayıları: ss.769-784
  • Anahtar Kelimeler: collaborative data gathering, construction safety, electroencephalogram (EEG), emotional intelligent, machine learning, project management
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

This article proposes an emotionally intelligent construction safety monitoring model that integrates machine learning and expert-informed Electroencephalogram (EEG)-related features as brain wave measurement device. The proposed safety prediction model is trained with risky behaviours, related emotional states, and expert-informed EEG-related features, incorporating brain waves and corresponding cortex locations. The architecture of the proposed emotionally intelligent safety monitoring system is detailed, utilizing real-world construction datasets and questionnaires. The value of the proposed emotionally informed ML framework lies in introducing EEG-related emotional constructs into construction safety assessment through an exploratory, expert-informed representation of emotional intelligence. The addition of a new dimension to the construction safety prediction models and consideration of the versatility of factoring in emotional states makes implications of this study beyond safety to other fields of construction management areas.