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AI for Good Innovate for Impact

Use Case 14: CargoWaves: The AI-Driven Inland Transport Platform

Designed to Transform Logistics and Transport Industry 4.5: Manufacturing

Country: United Arab Emirates

Organization: DP World Country

Contact Person(s): Sabeen Muhammad – Sabeen.Muhammad@ dpworld .com,

Secondary contact: Marwa Iqbal Mir Khoory – Marwa.Khoory@ dpworld .com, +971-4-8896789

1 Use Case Summary Table

Item Details

Category Manufactu
Problem Previously, inland transport was plagued by inefficiencies such as manual
Addressed truck booking, high dependency on brokers, limited real-time tracking,
and excessive empty runs. These inefficiencies led to increased costs,
delays, and environmental impact. By leveraging AI to optimize transport
operations, Cargowaves eliminates fragmentation, reduces costs, and
enhances sustainability, shaping the future of smart logistics.
Key Aspects of Optimization of the booking process
Solution • Tracking of the movement container from loading to delivery.
• Improved visibility of truck movements in the port for the terminal
operations department.
• Enhanced milestone notification to all the relevant parties involved.
• Improved driver and terminal ops communication for support
purposes.
• The key aspects of AI used in the solution were the Haulier recom-
mendation model, Time slot Recommendation Models

Technology Python, Rust, NextJS, PostgreSQL, XGBoost
Keywords

Data Availability Private
Standards We adhere to ISO 27001 for ISMS in implementing our solutions &
CRISP(Cross industry Standard Process)-ML (for AI model development)
Input – Text-based via web
Metadata (Type of Text (Relational Data)
Data)

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