The knowlEdge project and Decentralised Technical Intelligence (DTI) – Implications for transport economics

Description

The knowlEdge project (2021 – 2024) focused on transforming manufacturing and supply chain operations through the application of advanced computational techniques. By integrating real-time data processing and intelligent decision-making systems, the project aimed to enhance efficiency, flexibility, and responsiveness within supply chains. This was achieved through intelligent resource planning and adaptive scheduling, increased operational efficiency and reduced faulty output, ensuring optimal resource utilisation and reduced operational costs.

Decentralised Technical Intelligence (DTI) refers to the deployment of AI and machine learning algorithms in a distributed manner across various network nodes and stressing human involvement, allowing for local data processing and autonomous decision-making without relying on a central authority. The knowlEdge project embodied DTI concepts by enabling decentralised, real-time optimisation of supply chain activities. This approach not only improves operational efficiency but also enhances the resilience and adaptability of supply chains in the face of disruptions.

Transport economics, fundamentally concerned with the efficient allocation of resources in the transport sector, could be significantly impacted by the integration of DTI within production management and supply chains. The knowlEdge project demonstrated that DTI can lead to cost reductions, improved service quality and enhanced environmental sustainability within production and related transportation and logistical activities. By improving operations and reducing emissions through intelligent management, DTI supports more sustainable and economically viable transport systems. Additionally, smarter infrastructure investment driven by data insights, also originating from production systems data exchange, ensures that transport networks evolve in line with actual demand, further boosting economic efficiency.

Period	26 Jul 2024
Event title	ECTRI TG Ecopol Webinar
Event type	Webinar