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Rosak-Szyrocka / Wolniak / Grebski

Human-Centered Artificial Intelligence For Industrial Safety

Medium: Buch
ISBN: 978-1-041-26952-6
Verlag: Taylor & Francis Ltd
Erscheinungstermin: 22.09.2026
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This book examines the transformative role of artificial intelligence (AI) in industrial safety, focusing on the shift from traditional reactive systems to proactive, predictive safety architectures in smart factories. It explores how AI technologies, including machine learning, computer vision, biometrics, wearables, augmented reality, and digital twins, are revolutionising occupational health and safety across industries such as manufacturing, logistics, energy, aviation, and construction. The book highlights the integration of AI-enabled safety systems, addressing real-time risk monitoring, predictive maintenance, employee well-being, and accident prevention. It also delves into the ethical, legal, and regulatory implications of AI in safety-critical systems, including GDPR compliance, algorithm transparency, and ISO 45001 standards. Case studies from global companies like Siemens, Boeing, Samsung, and INVISTA provide practical insights into implementation, challenges, and outcomes.

Produkteigenschaften

  • Artikelnummer: 9781041269526
  • Medium: Buch
  • ISBN: 978-1-041-26952-6
  • Verlag: Taylor & Francis Ltd
  • Erscheinungstermin: 22.09.2026
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2026
  • Serie: Knowledge-based Engineering for Innovation
  • Produktform: Gebunden
  • Gewicht: 530 g
  • Seiten: 202
  • Format (B x H x T): 156 x 234 x 13 mm
  • Ausgabetyp: Kein, Unbekannt

Themen

Autoren/Hrsg.

Autoren

PART 1 - FOUNDATIONS OF AI-DRIVEN SAFETY IN SMART FACTORYChapter 1. Workplace safety in the AI era1.1. The Evolution of Safety Systems: from Reactive to Predictive1.2. Human-Centered Safety in industry 4.0 and 5.01.3. Modern Safety Culture in an Era of Data and AutomationChapter 2. Key AI Technologies for Safety System2.1. ML and AD Algorithms2.2. Edge Computing, Internet of Things, and Real Time Processing2.3. Digital Twins and cascading safety architectureChapter 3. Intelligent Hazard Sensing and Environmental Screening3.1. Intelligent Sensor Networks and Data Fusion3.2. Edge-Based Analytics and Latency-Free Alerts3.3. Integration with SCADA and Predictive MaintenancePART 2 - MODERN APPLIED TECHNOLOGIES AND INDUSTRIAL SOLUTIONSChapter 4. Wearable Technology and Worker-Focused Safety Monitoring4.1. Fall Detection, Fatigue Monitoring and Biometric Feedback4.2. Wearables-to-safety dashboard Integration4.3. Worker privacy, ethics, and real-time responseChapter 5. AR-enhanced Operational and Safety Support5.1. Augmented Interfaces and Field-of-Vision Alerts5.2. AR for industrial training and procedural assistance5.3. AR Powered Remote Support and Error ReductionChapter 6. AI-Powered Exoskeletons and Ergonomic Support6.1. Biomechanical Monitoring and Dynamic Support6.2. Task-Specific Adaptation and User Feedback6.3. Strategies for Long-term Health and Injury PreventionChapter 7. Computer Vision and Image Analytics for Industrial Safety7.1. Deep Learning for PPE Adherence Tracking7.2. Real-Time Video Stream for Unsafe Behaviour Detection7.3. Annotation, FPs, and Ethical Deployment Chapter 8. Real Time Localization and Obstacle Avoidance8.1. RTLS for Tracking Employee and Machine Movements8.2. Models of Collision Prediction and Mapping of Risk Zones8.3. Dynamic emergency alerts and situation awareness of the environmentPART 3 - FUTURE OF SAFETYChapter 9. Ethical, Privacy & Regulatory Considerations for AI Safety Systems9.1. Algorithmic Accountability and Explainability (XAI)9.2. GDPR, ISO 45001 and the AI Act in Practice in the Industry9.3. Participatory Privacy-Preserving Safety System DesignChapter 10. Workplace Safety in Industry 5.0: Customization, Collaboration and Sustainability10.1. Emotional AI and Worker-Centered Design10.2. Adaptive systems of inclusion and Variability10.3. Health and Safety within ESG and Human Capital Policies