Page 553 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

• End-to-End Digital Order Management: Automates requests to final delivery, reducing
manual processes.
• Load Consolidation Optimization: AI reduces empty haulage by 30%, maximizing truck
utilization.
• Real-Time Tracking: Enhances cargo visibility, improving yard planning and traffic 4.5: Manufacturing
management.
• AI-Based Terminal Slot Recommendations: Ensures just-in-time communication, reducing
wait times and enabling faster truck turnaround (up to 50%).
• Automated Order Processing: Cuts processing time by 50% by auto-drafting cargo
orders, reducing redundancy and errors.
• Digital Truck Booking: Reduces booking time by up to 90% through automation.
• Technical explanation:

o The algorithm used was the XGBoost classifier, which is based on supervised learning
o The Input features are related attributes that impact the selection of the hauliers.
The following features, container_iso_code, container_size, container_iso_type, and
container_weight, have been identified as key features for matching a hauler with a
Cargo owner
o The historical data is related to transactions done in the port by the hauliers for various
Cargo Owners
o The SMOTE technique was used to address the issue of imbalanced data in question.
o We adhere to ISO27001, ISO20000 ,and Dubai Data law

Impact on Intelligent Transport:

The initiative supports responsible and efficient resource use by integrating intelligent transport
systems that reduce waste and optimize operations across logistics and mobility networks.
By applying AI and data-driven decision-making, it ensures more efficient fuel use, reduced
emissions, and better asset utilization, promoting sustainable practices in transport and
infrastructure.

It also contributes to creating safer and more productive working environments through
automation and intelligent monitoring. Enhanced visibility into transport operations and worker
safety enables faster response to hazards and supports well-being in industrial and urban
settings.

By embedding cutting-edge technologies—such as AI, IoT, and real-time analytics—into
transportation systems, the initiative drives innovation across infrastructure and mobility sectors.
It helps develop resilient, adaptable, and future-ready networks capable of handling growing
urban and industrial demands.

Cargowaves enhances efficiency by automating workflows and leveraging AI-driven scheduling,
reducing manual labor and errors by up to 80%. Faster transaction times— improved by
75%—boost economic productivity, enabling transporters to scale operations. The platform
accelerates cargo throughput by 30%, lowers transport costs, and cuts idle truck hours by 50%,
strengthening regional trade and business competitiveness.

AI-powered load matching and 100% paperless workflows modernize inland transport. By
minimizing empty hauls by 30%, Cargowaves enhances industry resilience and optimizes
infrastructure usage. Its predictive analytics help terminals manage traffic patterns, reduce
idle time, and improve port efficiency, fostering a smarter, more sustainable logistics network.

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