From the article: Abstract—By using agent technology, a versatile and modular monitoring system can be built. In this paper, such a multiagentbased monitoring system will be described. The system can be trained to detect several conditions in combination and react accordingly. Because of the distributed nature of the system, the concept can be used in many situations, especially when combinations of different sensor inputs are used. Another advantage of the approach presented in this paper is the fact that every monitoring system can be adapted to specific situations. As a case-study, a health monitoring system will be presented.
Over the last years a large growth in Electric Vehicles (EV) and charging infrastructure (CI) development has been observed. Particularly in metropolitan areas this growth has led to a system in which multitudes of interactions between EV users take place. While many researchers have focused on EV user charging behavior and deployment strategies for CI, little attention has been paid to conceptualizing the problem domain. This research provides a brief overview of complex systems theory, and derives six characterizing elements of complex systems that may be applicable for CI. The paper investigates both theoretically but also empirically how these characterizing elements apply for CI and provides implications for the further roll-out of CI for both policy makers and researchers. We illustrate our findings with preliminary results form ongoing research. Recommendations include the further development of simulation tools that are capable of exploring effects of e.g. non-linear behavior, feedback loops and emergence of new patterns on CI performance. In the end this paper aims to provide directions to enable policy makers to be better prepared for the anticipated exponential growth of EVs and CI.
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The increasing rate of urbanization along with its socio-environmental impact are major global challenges. Therefore, there is a need to assess the boundaries to growth for the future development of cities by the inclusion of the assessment of the environmental carrying capacity (ECC) into spatial management. The purpose is to assess the resource dependence of a given entity. ECC is usually assessed based on indicators such as the ecological footprint (EF) and biocapacity (BC). EF is a measure of the biologically productive areas demanded by human consumption and waste production. Such areas include the space needed for regenerating food and fibers as well as sequestering the generated pollution, particularly CO2 from the combustion of fossil fuels. BC reflects the biological regeneration potential of a given area to regenerate resources as well to absorb waste. The city level EF assessment has been applied to urban zones across the world, however, there is a noticeable lack of urban EF assessments in Central Eastern Europe. Therefore, the current research is a first estimate of the EF and BC for the city of Wrocław, Poland. This study estimates the Ecological Footprint of Food (EFF) through both a top-down assessment and a hybrid top-down/bottom-up assessment. Thus, this research verifies also if results from hybrid method could be comparable with top-down approach. The bottom-up component of the hybrid analysis calculated the carbon footprint of food using the life cycle assessment (LCA) method. The top-down result ofWrocław’s EFF were 1% greater than the hybrid EFF result, 0.974 and 0.963 gha per person respectively. The result indicated that the EFF exceeded the BC of the city of Wrocław 10-fold. Such assessment support efforts to increase resource efficiency and decrease the risk associated with resources—including food security. Therefore, there is a need to verify if a city is able to satisfy the resource needs of its inhabitants while maintaining the natural capital on which they depend intact. Original article at: https://doi.org/10.3390/resources7030052 © 2018 by the authors. Licensee MDPI.
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