No abstract

Nowadays, buildings are increasingly expected to meet higher and more complex performance requirements. Among these requirements, energy efficiency is recognized as an international goal to promote energy sustainability of the planet. Different approaches have been adopted to address this goal, the most recent relating consumption patterns with human occupancy. In this work, we analyze what are the main parameters that should be considered to be included in any building energy management. The goal of this analysis is to help designers to select the most relevant parameters to control the energy consumption of buildings according to their context, selecting them as input data of the management system. Following this approach, we select three reference smart buildings with different contexts, and where our automation platform for energy monitoring is deployed. We carry out some experiments in these buildings to demonstrate the influence of the parameters identified as relevant in the energy consumption of the buildings. Then, in two of these buildings are applied different control strategies to save electrical energy. We describe the experiments performed and analyze the results. The first stages of this evaluation have already resulted in energy savings of about 23% in a real scenario.

Abstract-This paper presents the main foundations of Big Data applied to Smart Cities. A general Internet of Things based architecture is proposed to be applied to different smart cities applications. We describe two scenarios of big data analysis. One of them illustrates some services implemented in the smart campus of the University of Murcia. The second one is focused on a tram service scenario where thousands of transit-card transactions should be processed. Results obtained from both scenarios show the potential of the applicability of this kind of techniques to provide profitable services of smart cities, such as the management of the energy consumption and comfort in smart buildings, and the detection of travel profiles in smart transport.

Over six billion people are expected to live in cities and surrounding regions by 2050. Consequently, in the near future, the autonomic and smart operation of cities may be a critical requirement to improve the economic, social, and environmental well‐being of citizens. Smart urban technologies represent an important contribution to the sustainable development of cities, making smart cities a reality. In this sense, the energy sustainability of cities has become a global concern, bringing with it a wide range of research and technological challenges that affect many aspects of people's lives. Because most of the human lifetime is spent indoors, buildings, which make up a city subsystem, require special attention. Indeed, buildings are the cornerstone in terms of power consumption and CO2 emissions on a global scale. In this paper, we analyze the role that buildings play in terms of their energy performance at city level and present an energy‐efficient management system integrated in a building automation platform based on an Internet of Things approach. Occupants play a crucial role in the system's operation to achieve energy efficient building performance, and any impact on self‐sustainable smart cities will be a consequence of efficient user‐centric smart building designs. Our proposal represents a user‐centric smart solution as a contribution to the energy sustainability of modern cities. The building management platform has been deployed in a real (smart) building, in which a set of tests were carried out to assess different concerns involved in the building's infrastructure management. The first stages of this experiment have already resulted in an energy saving in heating of about 20% at building level, which could translate into a reduction of 8% in the energy consumption of buildings at a European city level. Copyright © 2013 John Wiley & Sons, Ltd.

No abstract