spChains: A Declarative Framework for Data Stream Processing in Pervasive Applications

Pervasive applications rely on increasingly complex streams of sensor data continuously captured from the physical world. Such data is crucial to enable applications to ``understand'' the current context and to infer the right actions to perform, be they fully automatic or involving some user decisions. However, the continuous nature of such streams, the relatively high throughput at which data is generated and the number of sensors usually deployed in the environment, make direct data handling practically unfeasible. Data not only needs to be cleaned, but it must also be filtered and aggregated to relieve higher level algorithms from near real-time handling of such massive data flows. We propose here a stream-processing framework (spChains), based upon state-of-the-art stream processing engines, which enables declarative and modular composition of stream processing chains built atop of a set of extensible stream processing blocks. While stream processing blocks are delivered as a standard, yet extensible, library of application-independent processing elements, chains can be defined by the pervasive application engineering team. We demonstrate the flexibility and effectiveness of the spChains framework on two real-world applications in the energy management and in the industrial plant management domains, by evaluating them on a prototype implementation based on the Esper stream processo

What Would You Ask to Your Home if It Were Intelligent? Exploring User Expectations about Next-Generation Homes

Ambient Intelligence (AmI) research is giving birth to a multitude of futuristic home scenarios and applications; however a clear discrepancy between current installations and research-level designs can be easily noticed. Whether this gap is due to the natural distance between research and engineered applications or to mismatching of needs and solutions remains to be understood. This paper discusses the results of a survey about user expectations with respect to intelligent homes. Starting from a very simple and open question about what users would ask to their intelligent homes, we derived user perceptions about what intelligent homes can do, and we analyzed to what extent current research solutions, as well as commercially available systems, address these emerging needs. Interestingly, most user concerns about smart homes involve comfort and household tasks and most of them can be currently addressed by existing commercial systems, or by suitable combinations of them. A clear trend emerges from the poll findings: the technical gap between user expectations and current solutions is actually narrower and easier to bridge than it may appear, but users perceive this gap as wide and limiting, thus requiring the AmI community to establish a more effective communication with final users, with an increased attention to real-world deploymen

Enabling Machine Understandable Exchange of Energy Consumption Information in Intelligent Domotic Environments

In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontolog

Home Energy Consumption Feedback: A User Survey

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 display

dWatch: a Personal Wrist Watch for Smart Environments

Intelligent environments, such as smart homes or domotic systems, have the potential to support people in many of their ordinary activities, by allowing complex control strategies for managing various capabilities of a house or a building: lights, doors, temperature, power and energy, music, etc. Such environments, typically, provide these control strategies by means of computers, touch screen panels, mobile phones, tablets, or In-House Displays. An unobtrusive and typically wearable device, like a bracelet or a wrist watch, that lets users perform various operations in their homes and to receive notifications from the environment, could strenghten the interaction with such systems, in particular for those people not accustomed to computer systems (e.g., elderly) or in contexts where they are not in front of a screen. Moreover, such wearable devices reduce the technological gap introduced in the environment by home automation systems, thus permitting a higher level of acceptance in the daily activities and improving the interaction between the environment and its inhabitants. In this paper, we introduce the dWatch, an off-the-shelf personal wearable notification and control device, integrated in an intelligent platform for domotic systems, designed to optimize the way people use the environment, and built as a wrist watch so that it is easily accessible, worn by people on a regular basis and unobtrusiv

Modeling, Simulation and Emulation of Intelligent Domotic Environments

Intelligent Domotic Environments are a promising approach, based on semantic models and commercially off-the-shelf domotic technologies, to realize new intelligent buildings, but such complexity requires innovative design methodologies and tools for ensuring correctness. Suitable simulation and emulation approaches and tools must be adopted to allow designers to experiment with their ideas and to incrementally verify designed policies in a scenario where the environment is partly emulated and partly composed of real devices. This paper describes a framework, which exploits UML2.0 state diagrams for automatic generation of device simulators from ontology-based descriptions of domotic environments. The DogSim simulator may simulate a complete building automation system in software, or may be integrated in the Dog Gateway, allowing partial simulation of virtual devices alongside with real devices. Experiments on a real home show that the approach is feasible and can easily address both simulation and emulation requirement

JEERP: Energy Aware Enterprise Resource Planning

Ever increasing energy costs, and saving requirements, especially in enterprise contexts, are pushing the limits of Enterprise Resource Planning to better account energy, with component-level asset granularity. Using an application-oriented approach we discuss the different aspects involved in designing Energy Aware ERPs and we show a prototypical open source implementation based on the Dog Domotic Gateway and the Oratio ER

Design Recommendations for Smart Energy Monitoring: a Case Study in Italy

In the era of green energy and smart grids, the ability to access energy information and effectively analyze such data to extract key performance indicators is a crucial factor for successful building management. Energy data can in fact be exploited both in long-term policy adaptation and in shorter term habits modification, providing the basis for stable improvements of the overall efficiency of buildings and dwellings. To reach the ambitious goal of actually improving how buildings consume energy, four main challenges emerge from literature: (a) lack of skills and experience of energy managers, (b) complex and disparate data sets, which are currently blocking decision making processes, (c) mostly-manual work-flows that struggle to find relevant information into overwhelming streams of data sourced by monitoring systems, and (d) lack of collaborations between organizational departments. This paper provides deeper insights on these challenges, by investigating the kind of analysis currently performed by energy managers (in Italy) and the expectations they have if required to reason about systems that will be available within the next five years, and proposes design recommendations for next generation energy intelligence systems

Complex Event Processing for City Officers: A Filter and Pipe Visual Approach

Administrators and operators of next generation cities will likely be required to exhibit a good understanding of technical features, data issues, and complex information that, up to few years ago, were quite far from day-to-day administration tasks. In the smart city era, the increased attention to data harvested from the city fosters a more informed approach to city administration, requiring involved operators to drive, direct, and orient technological processes in the city more effectively. Such an increasing need requires tools and platforms that can easily and effectively be controlled by non-technical people. In this paper, an approach for enabling "easier" composition of real-time data processing pipelines in smart cities is presented, exploiting a visual and block-based design approach, similar to the one adopted in the Scratch programming language for elementary school students. The proposed approach encompasses both a graphical editor and a sound methodology and workflow, to allow city operators to effectively design, develop, test, and deploy their own data processing pipelines. The editor and the workflow are described in the context of a pilot of the ALMANAC European project

DogOnt as a viable seed for semantic modeling of AEC/FM

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