# AI Enhances Safety (for Cargo Tank Hazmat Offload at Semiconductor Factory)
## AI Machine Vision Prevents Hazardous Accidents Due to Human Error
- According to factory SOP
- Ensuring third-party and factory safety
- Immediate warning of any improper operation that compromises safety (REAL TIME)
Limitations of Traditional Monitoring Systems
Automated video monitoring systems are a tried-and-tested technique to improve compliance and worker safety. Still, hardware and software complexity, inflexibility, and compatibility issues with traditional rule-based monitoring systems often create more difficulties than they solve. The finicky setup is particularly hard to maintain for hazmat offloading because of environmental variables and the level of precision required for manual monitoring setup. For accurate monitoring, the tanker must stop in precisely the same position every time. Even then, different types of tankers and lighting conditions could cause incorrect judgment by rule-based algorithms. When operators move around the tanker, the viewing angle and position also changes, a further challenge to accurate judgment by traditional algorithms. This combination of factors makes accurate real-time monitoring almost impossible and limits the surveillance system to passive video recording, rather than actively monitoring and alerting to potential trouble, and preventing possible tragedy.
AI Bolsters Monitoring Capabilities
The features shown in this demo are
- Custom virtual restricted areas
- Traffic cones detection
- Wear detection
Neon unbox > Experience by EVA IDE > Customize the logical> Train your own AI model
Step 1. Neon AI Smart Camera Starter Kit Unboxing
Step 2. Experience by EVA IDE
Step 3. Customize the logical
Step 4. Train your own AI model
The sample code is uploaded on git .
Follow the video and train your own model based on situation.
You can try to train your AI model and modify your own application.