Data Aggregation, Fusion and Recommendations for Strengthening Citizens Energy-aware Behavioural Profiles

In this paper, ENTROPY platform, an IT ecosystem for supporting energy efficiency in buildings through behavioural change of the occupants is provided. The ENTROPY platform targets at providing a set of mechanisms for accelerating the adoption of energy efficient practices through the increase of the energy awareness and energy saving potential of the occupants. The platform takes advantage of novel sensor networking technologies for supporting efficient sensor data aggregation mechanisms, semantic web technologies for unified data representation, machine learning mechanisms for getting insights from the available data and recommendation mechanisms for providing personalised content to end users. These technologies are combined and provided through an integrated platform, targeting at leading to occupants' behavioural change with regards to their energy consumption profiles.Comment: To appear in the proceedings of Global IoT Summit 201

A European research roadmap for optimizing societal impact of big data on environment and energy efficiency

We present a roadmap to guide European research efforts towards a socially responsible big data economy that maximizes the positive impact of big data in environment and energy efficiency. The goal of the roadmap is to allow stakeholders and the big data community to identify and meet big data challenges, and to proceed with a shared understanding of the societal impact, positive and negative externalities, and concrete problems worth investigating. It builds upon a case study focused on the impact of big data practices in the context of Earth Observation that reveals both positive and negative effects in the areas of economy, society and ethics, legal frameworks and political issues. The roadmap identifies European technical and non-technical priorities in research and innovation to be addressed in the upcoming five years in order to deliver societal impact, develop skills and contribute to standardization.Comment: 6 pages, 2 figures, 1 tabl

Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations

Recently, tremendous interest has been devoted to develop data fusion strategies for energy efficiency in buildings, where various kinds of information can be processed. However, applying the appropriate data fusion strategy to design an efficient energy efficiency system is not straightforward; it requires a priori knowledge of existing fusion strategies, their applications and their properties. To this regard, seeking to provide the energy research community with a better understanding of data fusion strategies in building energy saving systems, their principles, advantages, and potential applications, this paper proposes an extensive survey of existing data fusion mechanisms deployed to reduce excessive consumption and promote sustainability. We investigate their conceptualizations, advantages, challenges and drawbacks, as well as performing a taxonomy of existing data fusion strategies and other contributing factors. Following, a comprehensive comparison of the state-of-the-art data fusion based energy efficiency frameworks is conducted using various parameters, including data fusion level, data fusion techniques, behavioral change influencer, behavioral change incentive, recorded data, platform architecture, IoT technology and application scenario. Moreover, a novel method for electrical appliance identification is proposed based on the fusion of 2D local texture descriptors, where 1D power signals are transformed into 2D space and treated as images. The empirical evaluation, conducted on three real datasets, shows promising performance, in which up to 99.68% accuracy and 99.52% F1 score have been attained. In addition, various open research challenges and future orientations to improve data fusion based energy efficiency ecosystems are explored

From efficiency to reduction

This book presents the results of the international research project CODALoop: Community Data Loop for Energy Conscious Lifestyles. It dissects the energy practices that make urban households demanding energy in their daily life and reveals the pathway towards reducing this energy demand. To unpack energy practices, the authors of this volume move away from efficiency problems studying the interaction between human and new technologies. Instead, they use a repertoire of different analytical instruments to study how interaction between humans, and between humans and data, change the social norms that shape energy needs. The volume offers a synthesis of a cross- disciplinary study of energy reduction carried out in three different countries through multiple methodological approaches. The project at the source of the book was funded under the Joint Program Initiative 'Urban Europe' and the ERA-net framework. To unpack energy practices, the authors of this volume move away from efficiency problems studying the interaction between human and new technologies. Instead, they use a repertoire of different analytical instruments to study how interaction between humans, and between humans and data, change the social norms that shape energy needs. The volume offers a synthesis of a cross- disciplinary study of energy reduction carried out in three different countries through multiple methodological approaches. The project at the source of the book was funded under the Joint Program Initiative 'Urban Europe' and the ERA-net framework

EnCOMPASS - An integrative approach to behavioural change for energy saving

This paper presents the research objectives of the enCOMPASS project, which aims at implementing and validating an integrated socio-technical approach to behavioural change for energy saving. To this end, innovative user-friendly digital tools will be developed to 1) make energy data consumption available and understandable for different types of users and stakeholders (household residents, office employees, school pupils, building managers, utilities, ICT providers) and to 2) empower them to collaborate in order to achieve energy savings and manage their energy needs in efficient, cost-effective and comfort-preserving ways. The project will demonstrate how this can be achieved with a novel approach that integrates user-centered visualisation of energy data from smart sensors and user-generated information with context-aware collaborative recommendations for energy saving, intelligent control and adaptive gamified incentives enabling effective and sustained behavioural change

Impact of Occupant Behaviour (OB) on building energy use and thermal comfort: From stochastic modelling and occupant profiling to interdisciplinary user engagement

L'abstract è presente nell'allegato / the abstract is in the attachmen