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Complementarities and synergies of quadruple helix innovation design in smart city development
(2020)
Increased urbanization trends are stimulating regional needs to support transitions from urban environments to smart cities, using its holistic perspective as a source to innovation. Strong relations between smart cities, urban and regional development, are getting increased attention both at policy and implementation level, providing fertile ground for execution of the new European policy frameworks that supports quadruple helix approaches to innovation. Smart specialization strategies (RIS3) encompass such initiatives, placing ICT and collaboration between academia, industry, government, and citizen at the center of urban innovation. However, there is still lack of research on effects of such approaches to innovation, involving both quadruple helix clusters and ICT in utilizing innovation potentials for developing smart cities. This study aims to increase the understanding on how quadruple helix urban innovation strengthens competitiveness of regions by improving its local smart areas – RIS3. We identified smart specialization patterns and applied comparative benchmark between nine smallmedium sized urban regions in Central Europe. Building on these results, the study provides an overview of the effects of RIS3 strategies implemented through quadruple helix innovation clusters on competitiveness of regions and Smart City development.
With the emergence of the recent Industry 4.0 movement, data integration is now also being driven along the production line, made possible primarily by the use of established concepts of intelligent supply chains, such as the digital avatars. Digital avatars – sometimes also called Digital Twins or more broadly Cyber-Physical Systems (CPS) – are already successfully used in holistic systems for intelligent transport ecosystems, similar to the use of Big Data and artificial intelligence technologies interwoven with modern production and supply chains. The goal of this paper is to describe how data from interwoven, autonomous and intelligent supply chains can be integrated into the diverse data ecosystems of the Industry 4.0, influenced by a multitude of data exchange formats and varied data schemas. In this paper, we describe how a framework for supporting SMEs was established in the Lake Constance region and describe a demonstrator sprung from the framework. The demonstrator project’s goal is to exhibit and compare two different approaches towards optimisation of manufacturing lines. The first approach is based upon static optimisation of production demand, i.e. exact or heuristic algorithms are used to plan and optimise the assignment of orders to individual machines. In the second scenario, we use real-time situational awareness – implemented as digital avatar – to assign local intelligence to jobs and raw materials in order to compare the results to the traditional planning methods of scenario one. The results are generated using event-discrete simulation and are compared to common (heuristic) job scheduling algorithms.