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

DogOnt - Ontology Modeling for Intelligent Domotic Environments

Abstract. Home automation has recently gained a new momentum thanks to the ever-increasing commercial availability of domotic components. In this context, researchers are working to provide interoperation mechanisms and to add intelligence on top of them. For supporting intelligent behaviors, house modeling is an essential requirement to understand current and future house states and to possibly drive more complex actions. In this paper we propose a new house modeling ontology designed to fit real world domotic system capabilities and to support interoperation between currently available and future solutions. Taking advantage of technologies developed in the context of the Semantic Web, the DogOnt ontology supports device/network independent description of houses, including both “controllable ” and architectural elements. States and functionalities are automatically associated to the modeled elements through proper inheritance mechanisms and by means of properly defined SWRL auto-completion rules which ease the modeling process, while automatic device recognition is achieved through classification reasoning.

SAT based Enforcement of Domotic Effects in Smart Environments

The emergence of economically viable and efficient sensor technology provided impetus to the development of smart devices (or appliances). Modern smart environments are equipped with a multitude of smart devices and sensors, aimed at delivering intelligent services to the users of smart environments. The presence of these diverse smart devices has raised a major problem of managing environments. A rising solution to the problem is the modeling of user goals and intentions, and then interacting with the environments using user defined goals. `Domotic Effects' is a user goal modeling framework, which provides Ambient Intelligence (AmI) designers and integrators with an abstract layer that enables the definition of generic goals in a smart environment, in a declarative way, which can be used to design and develop intelligent applications. The high-level nature of domotic effects also allows the residents to program their personal space as they see fit: they can define different achievement criteria for a particular generic goal, e.g., by defining a combination of devices having some particular states, by using domain-specific custom operators. This paper describes an approach for the automatic enforcement of domotic effects in case of the Boolean application domain, suitable for intelligent monitoring and control in domotic environments. Effect enforcement is the ability to determine device configurations that can achieve a set of generic goals (domotic effects). The paper also presents an architecture to implement the enforcement of Boolean domotic effects, and results obtained from carried out experiments prove the feasibility of the proposed approach and highlight the responsiveness of the implemented effect enforcement architectur

Exploiting Semantic Technologies in Smart Environments and Grids: Emerging Roles and Case Studies

Semantic technologies are currently spreading across several application domains as a reliable and consistent mean to address challenges related to organization, manipulation, visualization and exchange of data and knowledge. Different roles are actually played by these techniques depending on the application domain, on the timing constraints, on the distributed nature of applications, and so on. This paper provides an overview of the roles played by semantic technologies in the domain of smart grids and smart environments, with a particular focus on changes brought by such technologies in the adopted architectures, programming techniques and tools. Motivations driving the adoption of semantics in these different, but strictly intertwined, fields are introduced using a strong application-driven perspective. Two real-world case studies in smart grids and smart environments are presented to exemplify the roles covered by such technologies and the changes they fostered in software engineering processes. Learned lessons are then distilled and future adoption scenarios discussed

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

UniDA: Uniform Device Access Framework for Human Interaction Environments

Human interaction environments (HIE) must be understood as any place where people carry out their daily life, including their work, family life, leisure and social life, interacting with technology to enhance or facilitate the experience. The integration of technology in these environments has been achieved in a disorderly and incompatible way, with devices operating in isolated islands with artificial edges delimited by the manufacturers. In this paper we are presenting the UniDA framework, an integral solution for the development of systems that require the integration and interoperation of devices and technologies in HIEs. It provides developers and installers with a uniform conceptual framework capable of modelling an HIE, together with a set of libraries, tools and devices to build distributed instrumentation networks with support for transparent integration of other technologies. A series of use case examples and a comparison to many of the existing technologies in the field has been included in order to show the benefits of using UniDA

DoMAIns: Domain-based Modeling for Ambient Intelligence

Ambient Intelligence and Smart Home Automation systems are currently emerging as feasible and ready to exploit solutions to support more intelligent features inside future and current homes. Thanks to increased availability of off-the-shelf components and to relatively easy to implement solutions we are experiencing a steady evolution of households, causing an ever-increasing users’ awareness of the capabilities of such innovative environments. To foster effective adoption of Smart Home Automation technologies in our home environments, traditional architectural and plant design must be complemented by sound design methodologies and tools, supporting the whole environment design cycle, including for example modeling, simulation and emulation, as well as, when feasible, formal model-checking and verification. Several research efforts have already addressed the design of expressive modeling tools, mostly based on Semantic Web technologies, as well as of suitable platforms for adding interoperation and rule-based intelligence to home environments. This paper proposes a new modeling methodology designed to fit the different phases of Intelligent Environments design, with a particular focus on validation and verification of the whole system. Carefully designed separation of modeled entities permits to exploit the DoMAIns framework during all phases of the environment design, from early abstract conception to the final in-field deployment. The DoMAIns design methodology is applied to a sample use case that involves comprehensive modeling and simulation of a Bank Security Booth, including the environment, the control algorithms, the automation devices and the user. Results show that the approach is feasible and that can easily handle different types of environment modeling, required in the different design phases, and for each of them it may support simulation, emulation, or other verification techniques

A Semantics-Rich Information Technology Architecture for Smart Buildings

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

Towards a software infrastructure for district energy management

Nowadays ICT is becoming a key factor to enhance the energy optimization in our cities. At district level, real-time information can be accessed to monitor and control the energy distribution network. Moreover, the fine grain monitoring and control done at building level can provide additional information to develop more efficient control policies for energy distribution in the district. In this paper we present a distributed software infrastructure for district energy management, which aims to provide a digital archive of the city in which energetic information is available. Such information is considered as the input for a decision system, which aims to increase the energy efficiency by promoting local balancing and shaving peak loads. As case study, we integrated in our proposed cloud the heating distribution network in Turin and we present exploitable options based on real-world environmental data to increase the energy efficiency and minimize the peak reques