Optimal-LOADS project aims to enhance multi-modal logistics supply chains by integrating data-driven services, digitizing port operations, and enabling secure data exchange. It focuses on AI-based decision-making, promoting environmental sustainability, boosting economic competitiveness, and fostering innovation in the logistics and maritime sectors, while ensuring data sovereignty and security.
The main goals of the project:
- Optimize Logistics Processes: Enhance the efficiency and digitalization of logistics operations to ensure resilience in the supply chain.
- Data Sovereignty and Interoperability: Develop secure data spaces that ensure data control and enable seamless data exchange among stakeholders.
- Identification of similarities to former customer requests, offerings or projects by searching various heterogeneous data sources, like ERP, CRM, CAD systems and others,
- Boost Efficiency in Multi-Modal Logistics: Improve coordination and optimization across various logistics and transport modes.
- Promote Technological Innovation: Implement AI and data-driven analysis to enhance decision-making and drive technological advancements in logistics.
Some Project KPIs/Major Optimal-LOADS outcomes:
- Reduce maritime accidents by 10% through better congestion management.
- Increase profitability by reducing yearly operational costs by 10%.
- Demonstrate the use of data space components to exchange operational data currently in analogue form.
- Implement up to five different sensors via Data Space components.
- Integrate 1 local IoT platform with GAIA-X data space.
- Achieve 75% accuracy in AI-based water quality forecasts compared to monitored data.
Consortium Members:
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