Traficon (Finland)

Abstract PRESORT is a research project funded by the Conference of European Directors of Roads (CEDR) through the CEDR Transnational Road Research Programme (Call 2022). The aim is to improve the use of third-party data by National Road Authorities (NRAs). NRAs are seeing increasing levels of digitisation and are open to the potential opportunities through the utilisation of third-party data – that is, data aggregated from multiple sources – to support them in the delivery of their core business services in traffic management, asset management, and construction. PRESORT will eventually deliver practical, implementable, easy to use online guide to support NRAs to make better decisions regarding HOW and WHEN to acquire and use third-party data, which will assist their core business activities. The initial phase of this project involved capturing the current state of third-party data use by NRAs. Part of this phase explored the challenges and barriers NRAs face regarding use of third-party data through a literature review and engagement with data providers and crucially, the NRA end-users. This paper reports on the results of this engagement.

Abstract Real-time data from diverse Internet of Things (IoT) sensors (such as cameras, temperature, light, and air quality sensors) is essential for monitoring smart manufacturing environments. However, efficiently perceiving, integrating, and interpreting this data remains a challenge, as it involves dealing with heterogeneous data formats, ensuring data accuracy, and providing real-time analytics. This paper proposes a semantic-enhanced Digital Twin (DT) to address these complexities and aims to offer a comprehensive view of industrial working environments. The paper first presents a conceptual overview of the semantic-enhanced DT architecture, followed by a detailed description of the system architecture, encompassing edge, cloud, and interface modules. Additionally, the implementation of the entire system is presented. The results demonstrate the feasibility of the proposed DT, showing its potential for deployment in real-world scenarios.