Christos Goumopoulos

Ambient Ecologies in Smart Homes

An important characteristic of ubiquitous computing (UbiComp) environments is the integration of information, communication and sensing technologies into our everyday objects, giving rise to a new proactive computing model in homes. A smart home uses networked sensors, devices and appliances to build an intelligent environment in which many activities in the home are automated and where devices and services seamlessly cooperate to support domestic tasks. Programming and maintaining such an infrastructure is challenging because suitable abstractions are currently missing. In this work we have attempted to define ambient ecologies as a metaphor for modeling UbiComp applications, specify design patterns and programming principles and develop infrastructure to provide a paradigm of application engineering and tools to support ambient ecology designers, developers and end-users. We describe our model and the middleware architecture and present the engineering of applications in a smart home environment.

An ontology-driven system architecture for precision agriculture applications

Our research has been performed in the context of the EU-funded R&D project PLANTS. In this paper, we describe an ontology-driven architecture for developing systems that can be used in precision agriculture applications. Central to our approach is the use of an ontology, which views plants and associated computation as an integral part and allows the interaction of plants and artefacts in the form of synergistic mixed societies. PLANTS ontology sets up a conceptual framework that combines the knowledge about sensors, actuators and other domain concepts available, on the one hand, and the biological studies about plant stressing and sensing mechanisms and consequent plant behaviour, on the other hand, to make plants a proactive component of agricultural systems.

Ontology-Based Representation of UPnP Devices and Services for Dynamic Context-Aware Ubiquitous Computing Applications

Ontology and related technologies have been introduced into the Ambient Intelligence domain as a mean to provide declarative formal representations of the domain knowledge. The range of devices available in the scope of an Ambient Intelligence space becomes increasingly heterogeneous and at the same time ubiquitous. Hence there is a need to link the discovery, description and deployment of these ambient devices and their services with context and domain knowledge representations in order to facilitate an Ambient Intelligence space experience. The contribution of this work is an approach for bridging the gap between the non-semantic description mechanisms of XML based devices description protocols, such as UPnP, and the AmI domain knowledge representation. For this we design a prototype ontology-based representation for UPnP devices and services that provide a semantic linking between human-centric abstract description, and the software-centric concrete description that derives from the UPnP descriptors and is necessary to remotely execute method calls on devices. We also demonstrate the benefits of its use with a prototype implementation.

The PLANTS System: Enabling Mixed Societies of Communicating Plants and Artefacts

In this paper we discuss research work that enables the development of mixed societies of communicating plants and artefacts. PLANTS is an EU-funded Research and Development project, which aims to investigate methods of creating “interfaces” between artefacts and plants in order to enable people to form mixed, interacting (potentially co-operating) communities. Amongst others the project aims to develop hardware and software components that should enable a seamless interaction between plants and artefacts in scenarios ranging from domestic plant care to precision agriculture. This paper deals with the approach that we follow for the development of the homonymous system and discusses its architecture with special focus on describing the communication among artefacts and plants and on designing an ontology that provides a formal definition of the domain under consideration.

Using AI planning and late binding for managing service workflows in intelligent environments

In this paper, we present an approach to aggregating and using devices that support the everyday life of human users in ambient intelligence environments. These execution environments are complex and changing over time, since the devices of the environments are numerous and heterogeneous, and they may appear or disappear at any time. In order to appropriately adapt the ambient system to a users needs, we adopt a service-oriented approach; i.e., devices provide services that reflect their capabilities. The orchestration of the devices is actually realized with the help of Artificial Intelligence planning techniques and dynamic service binding. At design time, (i) a planning problem is created that consists of the users goal to be achieved and the services currently offered by the intelligent environment, (ii) the planning problem is then solved using Hierarchical Task Network and Partial-Order Causal-Link planning techniques, (iii) and from the planning decisions taken to find solution plans, abstract service workflows are automatically generated. At run time, the abstract services are dynamically bound to devices that are actually present in the environment. Adaptation of the workflow instantiation is possible due to the late binding mechanism employed. The paper depicts the architecture of our system. It also describes the modeling and the life cycle of the workflows. We discuss the advantages and the limit of our approach with respect to related work and give specific details about implementation. We present some experimental results that validate our system in a real-world application scenario.

Design Guidelines for Building a Wireless Sensor Network for Environmental Monitoring

Environmental monitoring is a critical process that demands accuracy, reliability and stability at the operation level. Monitoring variables such as temperature, humidity, barometric pressure, soil moisture and ambient light facilitates research in fields such as precision agriculture, habitat monitoring, weather monitoring etc. The use of wireless sensor networks (WSNs) provides a technology solution for dynamic and unattended environmental monitoring, under the condition that requirements such as efficient power management and system robustness are satisfied. This paper presents the design and implementation of a WSN for monitoring environmental variables and evaluates its effectiveness. Based on the acquired experience we describe how we have confronted certain problems such as network synchronization and data consistency and we provide certain design guidelines for building such a system.

Rule handling in the day-to-day resource management problem: an object-oriented approach

The day-to-day resource management problem is caused by a set of unexpected events which disturb the planned daily activities and thus change the long-term optimal schedule. The solution to this problem presupposes that all the regulations for the handling of resources in the particular application domain have been satisfied. In this paper, a new approach to handling the rules in the resource management problem is presented. An object-oriented application specific language that allows the flexible expression of the rules, as well as the corresponding rule handling subsystem are presented. The design of the whole system is based on a generic meta-model derived from the object-oriented paradigm. This makes the system applicable to a wide range of problem domains such as repairs management, airline and other transportation scheduling, school scheduling, etc. The system has been developed and tested as a subsystem of the DAYSY system, a day-to-day resource management system for the airline domain.

ATRACO: Adaptive and Trusted Ambient Ecologies

ATRACO is an EU funded R&D project that considers ambient ecologies consisting of people, context-aware artefacts and digital commodities (e.g., services and content). Members of the ecology are able to adapt to each other and form trusted ad hoc collaborations to achieve specific tasks resulting from the need to serve specific human goals. Our aim is to research the factors and develop the technologies that will lead to the realisation of such ecologies, following an interdisciplinary effort which involves Computer Science, HCI, AI, Control Theory and Sociology. Key factors of the ATRACO problem space to be examined include adaptation, interoperability, user interaction and dynamicity of trust. We focus our efforts on seeking abstractions and mechanisms for establishing trust relationships between its members and on devising adaptation mechanisms based on system behaviour modelling, supervisory control theory of discrete event systems and type-2 fuzzy systems.

Parallel Crew Scheduling in PAROS

We give an overview of the parallelization work done in PAROS. The specific parallelization objective has been to improve the speed of airline crew scheduling, on a network of workstations. The work is based on the Carmen System, which is used by most European airlines for this task. We give a brief background to the problem. The two most time critical parts of this system are the pairing generator and the optimizer. We present a pairing generator which distributes the enumeration of pairings over the processors. This works efficiently on a large number of loosely coupled workstations. The optimizer can be described as an iterative Lagrangian heuristic, and allows only for rather fine-grained parallelization. On low-latency machines, parallelizing the two innermost loops at once works well. A new “active-set” strategy makes more coarse-grained communication possible and even improves the sequential algorithm.

Efficient trip generation with a rule modeling system for crew scheduling problems

Trip generation is the most time consuming phase in the solution process of crew scheduling problems faced by large transportation companies such as airlines and railways. A large number of trips must be constructed while satisfying a complex set of regulations. In this paper, we present an efficient trip generation method that utilizes originally a rule modeling system in order to reduce the corresponding search space. Special pruning rules are defined using a high-level rule language, which also supports the modeling of the business regulations required in the scheduling process. In addition, the legality checking mechanism involved has been tuned to perform efficiently in order to cope with the vast amount of the legality checks required by the trip generator. The algorithms are tested as a module for a crew scheduling application satisfying the tight response time requirements of a production system. We present experimental results based on problems provided by a major European airline that validate the usefulness and applicability of our work.