Reaching into patients’ homes – participatory designed AAL services

Ambient Assisted Living (AAL) offers possibilities for promising new IT-based health care services that are resulting in new challenges for its design process. We introduce a novel approach for engineering AAL services (AALSDA) which combines methods from service engineering and participatory design. We demonstrate this approach by developing and implementing an electronic data capture system, NuTrack, for self-reporting of nutrition status. The approach uses different concepts for AAL service design and delivery: service engineering for standardizing and structuring service processes, reasonable IT-support for automation of parts of services that need no person–to-person interaction, participatory design to integrate end-users in the development process, and patient integration for personalizing and improving the depth of performance of service providers’ service delivery. For illustration, we present the case of chronic disease patients suffering from impaired fine motor skills. Our approach is applied in a pilot study with prototypes tested in focus groups and workshops with patients, caregivers and physicians. The results demonstrate good applicability and feasibility of the concept, and provide new insights for the future design, development and implementation of AAL services.     

A design process enabling adaptation in pervasive heterogeneous contexts

In the next decades, the growth in population aging will cause important problems to most industrialized countries. To tackle this issue, Ambient Assistive Living (AAL) systems can reinforce the well-being of elderly people, by providing emergency, autonomy enhancement, and comfort services. These services will postpone the need of a medicalized environment and will allow the elderly to stay longer at home. However, each elderly has specific needs and a deployment environment of such services is likely unique. Furthermore, the needs evolve over time, and so does the deployment environment of the system. In this paper, we propose the use of a model-based development method, the adaptive medium approach, to enable dynamic adaptation of AAL systems. We also propose improvements to make it more suited to the AAL domain, such as considering heterogeneity and a composition model. The paper includes an evaluation of the prototype implementing the approach, and a comparison with related work.     

Supporting decision making process with “ideal” software agents - What do business executives want?

According to Simon’s (1977) decision making theory, intelligence is the first and most important phase in the decision making process. With the escalation of information resources available to business executives, it is becoming imperative to explore the potential and challenges of using agent-based systems to support the intelligence phase of decision-making. This research examines UK executives’ perceptions of using agent-based support systems and the criteria for design and development of their “ideal” intelligent software agents. The study adopted an inductive approach using focus groups to generate a preliminary set of design criteria of “ideal” agents. It then followed a deductive approach using semi-structured interviews to validate and enhance the criteria. This qualitative research has generated unique insights into executives’ perceptions of the design and use of agent-based support systems. The systematic content analysis of qualitative data led to the proposal and validation of design criteria at three levels. The findings revealed the most desirable criteria for agent based support systems from the end users’ point view. The design criteria can be used not only to guide intelligent agent system design but also system evaluation.     

Toward a functional reference model for master data quality management

The quality of master data has become an issue of increasing prominence in companies. One reason for that is the growing number of regulatory and legal provisions companies need to comply with. Another reason is the growing importance of information systems supporting decision-making, requiring master data that is up-to-date, accurate and complete. While improving and maintaining master data quality is an organizational task that cannot be encountered by simply implementing a suitable software system, system support is mandatory in order to be able to meet challenges efficiently and make for good results. This paper describes the design process toward a functional reference model for master data quality management (MDQM). The model design process spanned several iterations comprising multiple design and evaluation cycles, including the model’s application in a participative case study at consumer goods manufacturer Beiersdorf. Practitioners may use the reference model as an instrument for the analysis, design and implementation of a company’s MDQM system landscape. Moreover, the reference model facilitates evaluation of software systems and supports company-internal and external communication. From a scientific perspective, the reference model is a design artifact; hence it represents a theory for designing information systems in the area of MDQM.     

MULTI-AGENT SYSTEMS FOR DECISION SUPPORT: A CASE STUDY IN THE TRANSPORTATION MANAGEMENT DOMAIN

This article describes how agent and knowledge technology can be used to build advanced software systems that support operational decision making in complex domains. In particular, we present an abstract architecture and design guidelines for agent-based decision support systems. We illustrate our approach with a case study in the transportation management domain.     

Specifying distributed multi-agent systems in chemical reaction metaphor

This paper presents an application of Chemical Reaction Metaphor (CRM) in distributed multi-agent systems (MAS). The suitability of using CRM to model multi-agent systems is justified by CRM's capacity in specifying dynamic features of multi-agent systems. A case study in an agent-based e-learning system (course material updating) demonstrates how the CRM based language, Gamma, can be used to specify the architectures of multi-agent systems. The effectiveness of specifying multi-agent systems in CRM from the view point of software engineering is further justified by introducing a transformational method for implementing the specified multi-agent systems. A computation model with a tree-structured architecture is proposed to base the design of the specified multi-agent system during the implementation phase. A module language based on the computation model is introduced as an intermediate language to facilitate the translation of the specification of multi-agent systems. The multicast networking technology pragmatizes the implementation of communications and synchronization among distributed agents. The paper also discusses the feasibility of implementing an automatic translation from the Gamma specification to a program in the module language. This work is supported by University of Houston-Downtown Organized Research Committee.     

Engineering framework for agent-based manufacturing control

MAS (multi-agent systems) and HMS (holonic manufacturing systems) are enabling the vision of the Plug & Play Factory and paving the way for future autonomous production systems. This paper reviews the state of the art in implementations of agent-based manufacturing systems, and identifies the lack of engineering tools as a technological gap for widespread industrial adoption of the paradigm. The lack of tools limits the implementation of agent-based manufacturing systems within reach of only a handful of domain experts. One of the current challenges for the design and implementation of intelligent agents is the simulation and visualization of the agent societies. This issue is significant as soon as the software agent is embedded into a mechatronic device or machine resulting in a physical intelligent agent with 3D-mechanical restrictions. These mechanical restrictions must be considered in the negotiations between agents in order to coordinate the execution of physical operations. This paper presents an engineering framework that contributes towards overcoming the identified technology gap. The framework consists of a comprehensive set of software tools that facilitate the creation, simulation and visualization of agent societies. The 3D framework is innovative in fully emulating the deployed agents, recreating multi-agent negotiations and societies that coordinate and execute control of assembly operations. The documented research describes the methodology for the 3D representation of individual physical agents, the related identified objects present in the interaction protocols, and the assembly features and clustering algorithms.     

Enabling personalisation of remote elderly assistance

One of the goals of Ambient Assisted Living (AAL) solutions is to extend the time that elderly people can live independently in their preferred environments by using ICT technologies for personal healthcare. However, in order to be optimal, remote monitoring services and health-related interventions should be strongly personalised to specific individuals’ requirements, preferences, abilities and motivations, which can vary among the elderly, and even dynamically evolve over time for the same person depending on changing user needs and context-dependent conditions. In this paper we present an End User Development (EUD) tool for the personalisation of context-dependent assistance by non-technical users in the AAL domain. In particular, we have considered applications for remotely monitoring and assisting elderly people at home through sending multimedia messages and reminders, as well as changing the state of various domestic appliances (e.g. lamps, heating system, TV) and devices available in the context surrounding the user. The design and development of the tailoring environment has been carried out in an iterative manner, informed by the feedback that was gathered through empirical evaluations done with older adults and caregivers.

     

Agent-based modeling and simulation of an autonomic manufacturing execution system

Production management systems must constantly deal with unplanned disruptive events and disturbances such as arrivals of rush orders, raw material shortage/delays or equipment breakdowns along with a multitude of interactions in the supply chain which constantly demand on-line task rescheduling and order execution control. For responsiveness and agility at the shop-floor, a distributed design for manufacturing execution systems is proposed based on autonomic units that fill the gap between production planning and shop-floor control. An interaction mechanism designed around the concept of order and resource agents implementing the monitor-analyze-plan-execution loop is described. Generative simulation modeling of an autonomic manufacturing execution system (@MES) is proposed in order to evaluate emerging behaviors and macroscopic dynamics in a multiproduct batch plant. Results obtained for an industrial case study using a simulation model of the proposed @MES are presented. The usefulness of agent-based modeling and simulation as a tool for distributed MESs design and to verify performance, stability and disturbance rejection capability of an interaction mechanism is highlighted.     

On the architecture of a human-centered CAD agent system

With an increasing role of computers in the design process, a strong foundation of the basic principles for building CAD systems is extremely necessary. This work describes the architecture of a CAD system from the perspective of the capabilities required to build a human centered CAD system. These capabilities have been reported as task-sharing, communication, transparency, design rationale and cognition. Existing systems for engineering design have been analyzed from the perspective of these capabilities and an agent-based system previously reported in literature has been extended to a new architecture to support three of the aforementioned capabilities. The proposed architecture is an amalgamation of multi-agent systems, the ACT-R cognitive architecture and fuzzy rule based Petri nets. The salient advantage of this architecture is that it focuses on the capabilities of design rationale, transparency and cognition together—something which has been missing from all the current works in literature and is unique to the domain of application of the software system, which in this case is engineering design. The other capabilities namely task sharing and communication can be incorporated from lessons learnt from human–computer interaction research. The effectiveness of the proposed architecture is demonstrated by a hypothetical design case along with its implementation.     

MamMoeT: An intelligent agent-based communication support platform for multimodal transport

In this paper, an intelligent agent-based communication support platform for multimodal transport is developed. The rationale for doing so is found in the potential of such a system to increase cost efficiency, service and safety for different transport-related actors. Although, at present several comparable systems exist, their current implementation is far from successful because of technological and economic obstacles. The new expert communication platform put forward here (called MamMoeT) addresses these two issues by using a software agent-based approach. Software agents are pieces of software representing a single user. They are autonomous, communicative and intelligent. The MamMoeT system developed can be described as a real-time decision support system in which intelligent software agents handle communicative tasks, exchange desired amounts of information among different users using common exchange protocols which act as translators between different systems.     

A new approach in development of distributed framework for automated software testing using agents

Software testing is the technical kernel of software quality engineering, and to develop critical and complex software systems not only requires a complete, consistent and unambiguous design, and implementation methods, but also a suitable testing environment that meets certain requirements, particularly, to face the complexity issues. Traditional methods, such as analyzing each requirement and developing test cases to verify correct implementation, are not effective in understanding the software’s overall complex behavior. In that respect, existing approaches to software testing are viewed as time-consuming and insufficient for the dynamism of the modern business environment. This dynamics requires new tools and techniques, which can be employed in tandem with innovative approaches to using and combining existing software engineering methods. This work advocates the use of a recently proposed software engineering paradigm, which is particularly suited to the construction of complex and distributed software-testing systems, which is known as Agent-Oriented Software Engineering. This methodology is a new one, which gives the basic approach to agent-based frameworks for testing.     

Model-driven agent-based simulation development: A modeling language and empirical evaluation in the adaptive traffic signal control domain

Model-driven development (MDD) is an approach for supporting the development of software systems, in which high-level modeling artifacts drive the production of time and effort-consuming low-level artifacts, such as the source code. Previous studies of the MDD effectiveness showed that it significantly increases development productivity, because the development effort is focused on the business domain rather than technical issues. However, MDD was exploited in the context of agent-based development in a limited way, and most of the existing proposals demonstrated the effectiveness of using MDD in this context by argumentation or examples, lacking disciplined empirical analyses. In this paper, we explore the use of MDD for agent-based modeling and simulation in the adaptive traffic signal control (ATSC) domain, in which autonomous agents are in charge of managing traffic light indicators to optimize traffic flow. We propose an MDD approach, composed of a modeling language and model-to-code transformations for producing runnable simulations automatically. In order to analyze the productivity gains of our MDD approach, we compared the amount of design and implementation artifacts produced using our approach and traditional simulation platforms. Results indicate that our approach reduces the workload to develop agent-based simulations in the ATSC domain.     

ManufAg: a multi-agent-system framework for production control of complex manufacturing systems

In this paper, we present a framework for the implementation of multi-agent-systems for production control of complex manufacturing systems. We present the results of a requirement analysis for production control systems for complex manufacturing systems; then we describe the framework design criteria. Our framework supports the inclusion of distributed hierarchical decision-making schemes into the production control. Furthermore, in order to increase the coordination abilities of multi-agent-systems, we follow the decision-making and staff agent architecture suggested in the PROSA reference architecture. We indicate the usage of the framework for designing and implementing an agent-based production control system for semiconductor manufacturing processes in a case study.     

Modelling socio-ecological systems with MAIA: A biogas infrastructure simulation

Similar to other renewable energy technologies, the development of a biogas infrastructure in the Netherlands is going through social, institutional and ecological evolution. To study this complex evolutionary process, we built a comprehensive agent-based model of this infrastructure. We used an agent-based modelling framework called MAIA to build this model with the initial motivation that it facilitates modelling complex institutional structures. The modelling experience however proved that MAIA can also act as an integrated solution to address other major modelling challenges identified in the literature for modelling evolving socio-ecological systems. Building on comprehensive reviews, we reflect on our modelling experience and address four key challenges of modelling evolving socio-ecological systems using agents: (1) design and parameterization of models of agent behaviour and decision-making, (2) system representation in the social and spatial dimension, (3) integration of socio-demographic, ecological, and biophysical models, (4) verification, validation and sensitivity analysis of such ABMs.     

An empirical study of modeling self-management capabilities in autonomic systems using case-based reasoning

Autonomic systems promise to inject self-managing capabilities in software systems. The major objectives of autonomic computing are to minimize human intervention and to enable a seamless self-adaptive behavior in the software systems. To achieve self-managing behavior, various methods have been exploited in past. Case-based reasoning (CBR) is a problem solving paradigm of artificial intelligence which exploits past experience, stored in the form of problem–solution pairs. We have applied CBR based modeling approach to achieve autonomicity in software systems. The proposed algorithms have been described and CBR implementation on externalization and internalization architectures of autonomic systems using two case studies RUBiS and Autonomic Forest Fire Application (AFFA) have been shown. The study highlights the effect of 10 different similarity measures, the role of adaptation and the effect of changing nearest neighborhood cardinality for a CBR solution cycle in autonomic managers. The results presented in this paper show that the proposed CBR based autonomic model exhibits 90–98% accuracy in diagnosing the problem and planning the solution.     

An empirical study of modeling self-management capabilities in autonomic systems using case-based reasoning

Autonomic systems promise to inject self-managing capabilities in software systems. The major objectives of autonomic computing are to minimize human intervention and to enable a seamless self-adaptive behavior in the software systems. To achieve self-managing behavior, various methods have been exploited in past. Case-based reasoning (CBR) is a problem solving paradigm of artificial intelligence which exploits past experience, stored in the form of problem–solution pairs. We have applied CBR based modeling approach to achieve autonomicity in software systems. The proposed algorithms have been described and CBR implementation on externalization and internalization architectures of autonomic systems using two case studies RUBiS and Autonomic Forest Fire Application (AFFA) have been shown. The study highlights the effect of 10 different similarity measures, the role of adaptation and the effect of changing nearest neighborhood cardinality for a CBR solution cycle in autonomic managers. The results presented in this paper show that the proposed CBR based autonomic model exhibits 90–98% accuracy in diagnosing the problem and planning the solution.     

A goal-oriented,ontology-based methodology to support the design of AAL environments

One of the most critical issues in Ambient Assisted Living (AAL) is the design of systems that can evolve to meet the requirements of individuals as their needs and health conditions change. Although much work has been done on home and building automation systems for AAL, often referred to as assistive domotics, there is in fact still a substantial lack of solutions capable to support system designers in the early stage of development of such assistive systems. To this aim, the work contributes to the research on design of assistive domotic systems by presenting an ontology-driven methodology aimed to guide the development process. The novel contributions of the paper include the goal-oriented approach of the methodology, which involves the elicitation and analysis of AAL requirements and their formal representation in an ontology, where high-level goals are described in terms of subgoals and tasks, that are then linked to corresponding measures and devices. Moreover, logic-based reasoning enables more advanced functionalities useful at design time. We present a validation of the methodology showing typical use cases both related to the development from scratch of a domotic system with assistive capabilities starting from a set of high-level user requirements and the redesign of existing implementations according to changed requirements.     

The use of mTags for mandatory security: a case study

mTags is an efficient mechanism that augments inter‐thread messages with lightweight metadata. We introduce and discuss a case study that we have conducted in the use of mTags for realizing a kind of mandatory security. Although mTags can be implemented for any message passing thread‐based system, we consider an implementation of it in the POSIX‐compliant QNX Neutrino, a commercial microkernel‐based system. The approach to mandatory security that we adopt is Usable Mandatory Integrity Protection, which has been proposed in recent research. We call our adaptation of Usable Mandatory Integrity Protection using mTags, μMIP. We discuss the challenges we faced, and our design and implementation that overcomes these challenges. We discuss the performance of our implementation for well‐established benchmarks. We conclude with the observation that mTags can be useful and practical to realize mandatory security in realistic systems. Copyright © 2013 John Wiley & Sons, Ltd.