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This paper introduces euPOLIS; an EU funded project, which emphasize on the appropriate development of urban ecosystems in a way that enhance Public Health (PH) and Well-Being (WB) without significant Life-Cycle costs. Such an approach has has the potential to regenerate urban ecosystems addressing multiple challenges, such as low environmental quality, fragmentation and low biodiversity in public spaces, water-stressed resources, undervalued use of space in deprived areas resulting in an improved urban livability. The proposed methodology is expected to improve people’s quality of life, providing them with pleasant socializing open areas that stimulate social exchange while monitoring the impact of all those interventions to PH and WB of citizens. The euPOLIS suggested solutions will be demonstrated in 4 European cities: Belgrade, Lodz, Piraeus and Gladsaxe.

Targeted nature-based small-scale interventions is an approach commonly adopted by urban developers. The public acceptance of their implementation could be improved by participation, emphasizing residents or shopkeepers located close to the areas of interest. In this work, we propose a methodology that combines 3D technology, based on open data sources, user-generated content, 3D software and game engines for both minimizing the time and cost of the whole planning process and enhancing citizen participation. The proposed schemes are demonstrated in Piraeus (Greece) and Gladsaxe (Denmark). The core findings can be summarized as follows: (a) the time and cost are minimized by using online databases, (b) the gamification of the planning process enhances the decision making process and (c) the interactivity provided by the game engine inspired the participation of non-experts in the planning process (co-creation and co-evaluation), which decentralizes and democratizes the final planning solution.

Production lines need fast technologies for critical online decisions. Orchestration of different signals and processes from a number of different sensors around the industry, into related workflows are the key signals on workflows tasks recognition. The advantages of sensor networks' technologies outputs, that their outputs are controlled by multi agents systems, in order to orchestrate and execute related production workflows, is the main point of this research work. In specific, the aim of this manuscript is to present a system that manipulates and controls these workflows executions. System architecture and sub modules are presented in more detail through the manuscript, plus a production scenario implementation.