Search

The increasing complexity of the new breed of distributed intelligent systems, such as the Internet of Things, which require a diversity of languages and protocols, can only be tamed with design and programming best practices. Interest is also growing for including the human factor, as advocated by the "ambient intelligence" (AmI) research field, whose focus is on transparently and intelligently supporting people. These new design methodologies are increasingly needed in the toolbox of new electronic and computer engineers, and teaching strategies should be devised that allow students to acquire a systems-level view instead of getting lost in technology-oriented approaches. This paper describes a study carried out over two academic years, in a course in AmI at Politecnico di Torino, Italy. In the course, a project-based learning approach was adopted, in which students design and prototype an AmI system, and their progress is closely monitored throughout the semester. This paper presents the learning goals and teaching strategies, analyzes the learning outcomes from the qualitative and quantitative points of view, and highlights the lessons learned in the process.

Energy consumption and performance assessment of Smart Cities must consider different levels and various sub-domains. A comprehensive energy profile of a city, in fact, should work at the city, district, and building levels. At the same time and for each level, it should take into account both electrical and thermal consumptions, and gather these information from a plethora of different sensors and from various stakeholders (i.e., citizens, utilities, policy makers, and energy providers). Current modeling approaches for this context address each level and domain separately, thus preventing a structured and comprehensive approach to a unified energy representation. Moreover, current approaches make it difficult to keep the consistency between the energetic data through levels, sub-domains, and across stakeholders. Starting from an analysis of ontologies at the state-of-the-art, this paper shows how DogOnt can be used as a foundation towards a shared and unified model for such a context. DogOnt was firstly developed in 2008 and withstands over 8 years of usage without major failures and shortcomings. We discuss successful design choices and adaptations, which kept the model up-to-date and increasingly adopted in such a mid-term time frame for energy representation in Smart Cities. [ABSTRACT FROM AUTHOR]

A growing - yet debated - discussion around the negative aspects of overusing technology led researchers and practitioners to consider a new kind of psychological digital wellbeing, giving rise to the flourishing of digital self-control tools (DSCTs). As many people nowadays own and use several devices, there is a need to understand better their overlapping use (and non-use) and the relationships to digital wellbeing. This special issue aims to provide the academic and industry research communities a venue for work at the state-of-the-art on digital wellbeing and DSCTs, with a particular focus on digital wellbeing within complex technological and social contexts. [ABSTRACT FROM AUTHOR]

The increasing complexity of the new breed of distributed intelligent systems, such as the Internet of Things, which require a diversity of languages and protocols, can only be tamed with design and programming best practices. Interest is also growing for including the human factor, as advocated by the ambient intelligence (AmI) research field, whose focus is on transparently and intelligently supporting people. These new design methodologies are increasingly needed in the toolbox of new electronic and computer engineers, and teaching strategies should be devised that allow students to acquire a systems-level view instead of getting lost in technology-oriented approaches. This paper describes a study carried out over two academic years, in a course in AmI at Politecnico di Torino, Italy. In the course, a project-based learning approach was adopted, in which students design and prototype an AmI system, and their progress is closely monitored throughout the semester. This paper presents the learning goals and teaching strategies, analyzes the learning outcomes from the qualitative and quantitative points of view, and highlights the lessons learned in the process. [ABSTRACT FROM PUBLISHER]

The design of smart homes, buildings and environments currently suffers from a low maturity of available methodologies and tools. Technologies, devices and protocols strongly bias the design process towards vertical integration, and more flexible solutions based on separation of design concerns are seldom applied. As a result, the current landscape of smart environments is mostly populated by defectively designed solutions where application requirements (e.g., end-user functionality) are too often mixed and intertwined with technical requirements (e.g., managing the network of devices). A mature and effective design process must, instead, rely on a clear separation between the application layer and the underlying enabling technologies, to enable effective design reuse. The role of smart gateways is to enable this separation of concerns and to provide an abstracted view of available automation technology to higher software layers. This paper presents a blueprint for the information technology (IT) architecture of smart buildings that builds on top of established software engineering practices, such as model-driven development and semantic representation, and that avoids many pitfalls inherent in legacy approaches. The paper will also present a representative use case where the approach has been applied and the corresponding modeling and software tools. [ABSTRACT FROM AUTHOR]

Abstract: Buildings account for a relevant fraction of the energy consumed by a country, up to 20-40% of the yearly energy consumption. If only electricity is considered, the fraction is even bigger, reaching around 73% of the total electricity consumption, equally divided into residential and commercial dwellings. Building and Home Automation have a potential to profoundly impact current and future buildings’ energy efficiency by informing users about their current consumption patterns, by suggesting more efficient behaviors, and by pro-actively changing/modifying user actions for reducing the associated energy wastes. In this paper we investigate the capability of an automated home to automatically, and timely, inform users about energy consumption, by harvesting opinions of residential inhabitants on energy feedback interfaces. We report here the results of an on-line survey, involving nearly a thousand participants, about feedback mechanisms suggested by the research community, with the goal of understanding what feedback is felt by home inhabitants easier to understand, more likely to be used, and more effective in promoting behavior changes. Contextually, we also collect and distill users’ attitude towards in-home energy displays and their preferred locations, gathering useful insights on user-driven design of more effective in-home energy displays. [Copyright &y& Elsevier]