AI in dangerous goods logistics ‐ Recognizing potential, increasing safety
This workshop provides a practice-oriented overview of current and future fields of application for AI in dangerous goods handling.
Learning objectives
More security in handling:By using AI, errors in classification, packaging and documentation are detected at an early stage ‐ before they become safety-critical or expensive.
Time and cost savings:
Automated inspection processes reduce manual effort, speed up clearance and minimize delays.
Regulatory conformity and compliance:
NLP-based systems provide reliable support in complying with international dangerous goods regulations ‐ even with frequently changing regulations.
Contents
AI-supported processes in operational useLabel control with image recognition systems
-Precise identification and validation of the hazardous goods labels applied
-Reduction of human error sources through automated testing
Data-driven risk analysis
AI-supported decision-making: "Is this shipment releasable?"
Assessment of potential risks based on empirical values, patterns and real-time data
Seminar format
