Updatable multi-agent OSGi architecture for smart home system

2014

Smart Home is an emerging technology growing continuously which includes number of new technologies which helps to improve human’s quality of living. This paper proposes an adaptive home system for optimum utilization of power, through Artificial Intelligence and Wireless Sensor network. Artificial Intelligence is a technology for developing adaptive system that can perceive the enviornmrnt, learn from the environment and can make decision using Rule based system.Zigbee is a wireless sensor network used to efficiently deliver solution for an energy management and efficiency for adaptive home. An algorithm used in adaptive home system is based on software agent approach that reduce the energy consumption at home by considering the user’s occupancy, temperature and user’s preferences as input to the system.

2011

In this paper we propose an agent-based approach for controlling the behavior of a Smart Home Environment that, based on the recognized situation and user goal, selects a suitable workflow for combining services of the environment. To this aim we have developed a butler agent that employs user and context modeling for supporting proactive adaptation of the interaction with the house. The user can interact with the proposed services by accepting, declining or changing them. Such a feedback is exploited by the learning component of the butler to refine the user model and improve its future behavior accordingly. In order to provide a description of how the system might work, a practical example is shown.

The development of intelligent environments poses complex challenges, namely at the level of device heterogeneity and environment dynamics. In fact, we still lack supporting technologies and development approaches that can efficiently integrate different devices and technologies. In this paper we present how a recent integration of two important technologies, OSGi and Jade, can be used to significantly improve the development process, making it a more dynamic, modular and configurable one. We also focus on the main advantages that this integration provides to developers, from the Ambient Intelligence point of view. This work results from the development of two intelligent environments: VirtualECare, which is an intelligent environment for the monitorization of elderly in their homes and UMCourt, a virtual environment for dispute resolution.

IFAC-PapersOnLine, 2015

Health systems are evolving to cope with the increasing costs of providing high-level medical care to elderly people maintaining their quality of life. Smart homes, where ambient and biomedical sensors can coexist, have become a suitable approach to address the main goals of home care scenarios: preventive care, recognizing deteriorating health and allowing a personalized care. To achieve these goals, applications have to exhibit adaptability and availability among other characteristics. Adaptability allows tracking the patient's state as well as reacting to abnormal situations. Availability ensures the execution of the application under failure of processing devices. In order to meet these requirements, this paper proposes a general-purpose middleware architecture based on multi-agent technology that provides mechanisms to: develop customizable applications based on the separation of concerns principle; manage the execution of applications; support adaptability by means of event-based relationships among applications; ensure availability through the use of replicated agents. The performance of the proposed middleware is assessed in terms of reaction time to adapt to irregular situations for different availability levels (number of replicated agents) and number of application services.

2012

Abstract—This paper presents a system for home automation, called HORUS, which is based on an agent architecture. The benefits deriving from this type of solution are essentially three. Firstly, the agent paradigm provides a good abstraction mechanism for implementing a modular system, easy to configure according to the requirements of a specific application. The second reason is the possibility of scaling up to complex applications exploiting parallel and distributed computing on low power micro-pc. The third reason is load balancing and fault tolerance. When required, the agents migrate from one host to another providing fault tolerance and load balancing capabilities. Some agents are provided with learning capabilities and can learn the model on the environment where they operate. Finally, the agents communicate in xml over

Procedia Computer Science, 2012

This paper introduces a declarative agent-oriented language for Ambient Intelligence -S-CLAIM -that allows programming reactive or cognitive mobile agents in a simple, easy-to-use manner while meeting AmI requirements. Based on a hierarchical representation of the agents, the language offers a natural solution to achieve context-sensitivity. S-CLAIM is light-weight and, being transparently underpinned by the JADE framework, allows deployment on mobile devices and easy interoperation with other components by means of web services. The usefulness of the proposed language for AmI is illustrated through a scenario and a demo featuring an AmI application in a Smart Room.

2006

Smart-home conception has emerged in recent years and played a very important part in the formation of future houses. Since the beginning of the smart-home era, home automation benefits have never overshadowed the cost of such systems. One of these costs is that there is always the need for home inhabitants to program the system to perform daily tasks. In this paper we present prototype of a system that overcomes this problem by giving the home enough intelligence to adapt to its inhabitants life style without the need for the inhabitants to exercise authority. The system makes use of multi-agent and prediction techniques to provide intelligent smart-home appliances automation. Results indicate that the technique applied in this research not only makes the system very fast and accurate but also makes it portable and cost effective.

Lecture Notes in Computer Science, 2002

The last few years, a tendency arose to integrate various programmable devices through ever expanding computer networks. One particular domain in which this evolution stood out clearly is home automation. The EIB 1 standard defines a home automation solution that consists of a network of cooperating components with little computational power. Bridging the EIB network with a computer network allows software to interact with these EIB components. However, past attempts to link EIB components with computer networks fell short in dynamism, automatism or user friendliness. In this paper we present a distributed software framework that overcomes these issues, and is capable of automatically generating a software model based on the configuration of the components on the EIB fieldbus. A framework that can be used in this perspective is Jini. Its excellent capabilities for dynamic reconfiguration and its proven deployment in domestic and office environments make it an appropriate candidate for supporting home automation systems.

Service Oriented Computing and Applications, 2008

Service Oriented Architectures, which allow for the integration of different subsystems and of applications running on different devices and platforms, may be very suitable to solve the problem of service personalization in large smart environments like cities, where the number of potential users and potentially available services is rapidly growing. Taking this into account, we have designed an agent-based service oriented architecture for smart spaces. Two of the greatest challenges in the design of such a solution are providing effective device, service and context federation and composition mechanisms and handling user mobility. For the first challenge, we have designed a hierarchical architecture and developed a set of inheritance, aggregation and access mechanisms for devices, services and context. To handle user mobility, we have followed three different strategies, using stationary, mobile or nomadic agents. In this paper, we describe the main aspects of our architecture and perform an experimental evaluation to determine the advantages and drawbacks of the different strategies.

2022

The Internet of things (IoT) is currently contributing to a growing range of applications for intelligent environments by means of the interconnection of heterogeneous IoT smart devices over the Internet. Generally, smart devices are implemented through services (e.g., REST webservices) which can be consumed by other services or any other external application. In any case, services are essentially passive requiring necessarily another consuming software entity to be use. In this paper, the development of a new class of smart IoT device, called smart agent-based IoT device is proposed based on the implementation of software embedded agents. These agents can be executed proactively exploring the services, resources, devices, and even other agents located in the IoT environment to enhance the functionality of the smart agent-based device. In this way, we can improve overall system performance at runtime in a unaware IoT environment where IoT devices and available resources are not known a priori. In this paper, a description of the embedded agent model and the smart agent-based IoT device are outlined as well as how it is applied in the context of a smart home environment.