Cloud-Based Machine Learning for Maritime Logistics

In a leading port and maritime logistics operator company, employee exposure detection is crucial to avoid labor risks.

This study examines how a large online retailer utilized a cloud-based machine learning platform to train a deep learning model. The purpose of the model is to enhance labor security by detecting security equipment such as helmets and vests. The model helps detect security equipment like helmets and vests, making labor security better.

The client sought our AI consulting services to help. Project budget 200K and it lasted from June until August.

The company faced the challenge of maintaining labor security and complying with safety regulations in a high-risk environment. The manual detection of security equipment proved to be time-consuming and prone to errors. Workplace accidents were a concern, impacting employee morale and resulting in increased insurance costs.

To solve these problems, the company needed an AI strategy. They used a program from a big online retailer and manufacturer. It's a strong tool for training deep learning models.

Utilizing this technology, the company developed a robust object detection system capable of identifying security equipment like helmets and vests. This solution automated the detection process, reducing the reliance on manual inspections and improving the accuracy and efficiency of labor security protocols.

The implementation of object detection for security equipment yielded significant results. The company experienced a reduction in workplace accidents, ensuring the safety of its employees.

Thanks to AI consulting services, compliance with safety regulations improved, reducing the risk of penalties and litigation. The enhanced labor security protocols led to reduced insurance costs, resulting in substantial cost savings for the company.

Finally, the company boosted employees' morale and confidence, which fostered a safer and more productive work environment.