This paper introduces a multi-agent control system for a reconfigurable manufacturing system designed to provide, in the context of Industry 4.0, test-before-invest services by the FIT EDIH. The product assembled is flexible, with multiple possible assembly sequences. The manufacturing system is composed of multiple interchangeable manufacturing cells that allow any layout configuration with autonomous transporter units that move intermediate products from one cell to another. The reference architecture used to instantiate the developed prototype and its multi-agent control system with the required agents, concept and predicate ontology are subsequently presented. The hardware and software implementation are also detailed. The multi-agent system is implemented using SPADE framework. Each manufacturing cell is controlled using 4diac framework while transporters use Robot Operating System. Manufacturing orders are placed by a client using a web interface.

The authors of the paper have recently been involved in various projects related to the Internet of Things (IoT) and its practical application in several fields. These areas include Industry 4.0, smart cities, and healthcare - with a focus on behavior change. The projects used up to date technologies such as IoT, Machine Learning, Big Data, System of Systems (SoS) and Cloud Computing among others. The authors have specifically focused on specific IoT and SoS architectures, aiming to support and illustrate a variety of use cases. In this context, SoS expands the use of localized cloud, improving integration and communication technologies. It is essential that these SoS provide reliable quality of service (QoS), which includes management and monitoring of various QoS attributes.

Ageing is a multi-factorial physiological process and the development of novel IoT systems, tools and devices, specifically targeted to older people, must be based on a holistic framework built on robust scientific knowledge in different health domains. Furthermore, interoperability must be guaranteed using standardized frameworks or approaches. These aspects still largely lack in the specific literature. The main aim of the paper is to develop a new ontology (the NESTORE ontology) to extend the available ontologies provided by universAAL-IoT (uAAL-IoT). The ontology is based on a multidomain healthy ageing holistic model, structuring well-assessed scientific knowledge, specifically targeted to healthy older adults aged between 65 and 75. The tool is intended to support, and standardize heterogeneous data about ageing in compliance with the uAAL-IoT framework. The NESTORE ontology covers all the relevant concepts to represent 3 significant domains of ageing: (1) Physiological Status and Physical Activity Behaviour; (2) Nutrition; and (3) Cognitive and Mental Status and Social Behaviour. In total, 12 sub-ontologies were modelled with more than 60 classes and sub-classes referenced among them by using more than 100 relations and around 20 enumerations. The proposed ontology increases the uAAL collection by 40%. NESTORE ontology provides innovation both in terms of semantic content and technological approach. The thorough use of this ontology can support the development of a decision support system, to promote healthy ageing, with the capacity to do dynamic multi-scale modelling of user-specific data based on the semantic annotations of users’ profile.

Interoperability is complex non-functional requirement of any today' system, and it refers the exchanged information. Two systems must offer the possibility to exchange and use the data in order to be named "interoperable", meaning that the message sent must contain data (in a standard coded format) that can be interpreted by the system that will receive it. The next section describes the challenges encounter during the integration activities from the interoperability point of view for the next gen of systems that offer services at home.

In the context of the fourth revolution in healthcare technologies, leveraging monitoring and personalization across different domains becomes a key factor for providing useful services to maintain and promote well-being. This is even more crucial for older people, with aging being a complex multi-dimensional and multi-factorial process which can lead to frailty. The NESTORE project was recently funded by the EU Commission with the aim of supporting healthy older people to sustain their well-being and capacity to live independently. It is based on a multi-dimensional model of the healthy aging process that covers physical activity, nutrition, cognition, and social activity. NESTORE is based on the paradigm of the human-in-the-loop cyber-physical system that, exploiting the availability of Internet of Things technologies combined with analytics in the cloud, provides a virtual coaching system to support healthy aging. This work describes the design of the NESTORE methodology and its IoT architecture. We first model the end-user under several domains, then we present the NESTORE system that, analyzing relevant key-markers, provides coaching activities and personalized feedback to the user. Finally, we describe the validation strategy to assess the effectiveness of NESTORE as a coaching platform for healthy aging.

For decision-makers, a decision-making support is an essential component in any activity or industry. Decision Support Systems (DSS) provide decision-makers with functionalities to exploit various information on which to build a basis for making decisions. In the medical industry, specialized DSS are increasingly used to support physicians in making clinical decisions, thus helping to improve the medical services. The presented architecture make use of Electronic Health Record (EHR) combined with available technologies and standards, clinical databases and specialized knowledge bases. In the paper, it is presented a specialized DSS that answers the needs of the health system.

The interaction between a human operator and a machine is done through a Human Machine Interface. Nowadays many kinds of Human Machine Interfaces, for different types of machines, are available. Typically, visual, auditory and tactile human senses are used to connect the human to the machine. Even Brain-Computer Interfaces are developed, making this research field of high interest. In this paper we focus on the interaction between a human operator and an exoskeleton for addressing industrial needs. An assistive system for such an interaction is presented. Using a smartphone and interactive glasses, the presented system improves the human experience by offering easy control, personalization and monitoring for the exoskeleton. With this system, for steepening the learning curve, training materials are at a glance. Their purpose is to help the human to learn faster how to operate the exoskeleton and how to benefit from it.

The paper is about the use of new concepts and information technologies (IT) in the field of computer supported group decision-making. iDS (intelligent DecisionSupport), a practical IT platform that supports the activities in the group decision-making is used as a vehicle to illustrate the methodology and evolution of the solution adopted under the influence of new information technologies and practical applications. iDS has been designed and evolved to be useful, usable and used, by avoiding the need for complex training and preventing user rejection. It provides a collaborative working environment where group members can create and attend different types of decision sessions, named 'work sessions'. The iDS platform covers collaborative and group decision sessions, as well as individual decision sessions in a way that users on each decision stage are free to collaborate with other users.

Failure Mode and Effect Analysis (FMEA) is among the most widely used safety analysis procedures in the various industries. The procedure is generally perceived as complex and time-consuming, hindering an effective reuse of previous knowledge. In this paper we present a system that will improve the quality by capturing and reusing the knowledge circulated inside product design and development phase. The system proposed is an easy to use and proactive system that will complement and support the team members during the product design and development phase through the whole process in order to meet the quality requirements. There are tested and evaluated four algorithms used in textual case based reasoning and the conclusions are presented.

Abstract This paper presents innovative usage of knowledge system into Failure Mode and Effects Analysis (FMEA) process using the ontology to represent the knowledge. Knowledge system is built to serve multi-projects work that nowadays are in place in any manufacturing or services provider, and knowledge must be retained and reused at the company level and not only at project level. The system is following the FMEA methodology and the validation of the concept is compliant with the automotive industry standards published by Automotive Industry Action Group, and not only. Collaboration is assured trough web-based GUI that supports multiple users access at any time

Decision Support Systems have constantly benefited from the technological advances in Computer Science. Cloud Computing is a technology that could become useful for the Decision Support Systems, too. Moreover, Decision Support Systems may support the “global brain” programming paradigm. This paper presents iDS, a system designed to become a collaborative- and cloud-based Group Decision Support System. This Decision Support System will be made available as a Business as a Service model. After presenting the architecture of the developed iDS, the main design directions for integrating it into the cloud are described. The goal is to obtain a platform that supports collective intelligence, in terms of human-computer networking.

The increasing number of available collaborative tools and their extensive use in many organizational activities has constantly raised the complexity of collaboration engineering. It presumes the design of group decision processes, supported by a wide-range of groupware tools, in an ill-structured, dynamic, and open environment. As many of these processes are recurring by nature, the development of a shared repository to store the collective knowledge and experiences of group decision process designs became a core research topic of collaboration engineering in last few years. The paper presents a human–computer interaction engineering approach to design a software prototype that provides personalized, contextual and actionable recommendations for this problem. The approach emphasizes the computational aspects of collective intelligence, inspired from the stigmergic system designs, to structure these recommendations based on the collective knowledge that reflects not only the design space per se, but the collective experience in exploiting it as well. It is demonstrated by (1) detailing the engineering issues of an implemented prototype for the group decision process design; and (2) explaining its functionalities through a representative set of interaction scenarios. The paper covers the methodological, theoretical and practical aspects of engineering the above mentioned issues.

Group decision process design is a well-known class of ill-structured, dynamic, and going-concerns problem. The paper presents a human-computer interaction engineering approach to design a software prototype that provides personalized, contextual and actionable recommendations for this problem. The approach emphasizes the computational aspects of collective intelligence to structure these recommendations based on the collective knowledge that reflects not only the design space per se, but the collective experience in exploiting it as well. It is demonstrated by: 1) detailing the engineering issues of an implemented prototype for the group decision process design; and 2) explaining its functionalities through a representative set of interaction scenarios.

In the general context of Group Decision Support System (GDSS), the paper investigates the possibility to externalize and support from a metacognitive perspective the effective use of facilitation knowledge with self-development capabilities. The experimental results make evident that these capabilities may be easily engineered by adopting the basic principles of the design for emergence in constructing an e-meeting facilitation tool that act as a stigmergic collaborative environment for the participants. Basically, the GDSS needs to provide a minimal structure for modeling the group decision process (GDP) which enables a participant-driven approach to group facilitation and magnify the sense of social participation. In this way the GDSS may provide a collaborative environment where unpredictable and more effective models of GDP design will emerge through the exploration of the problem space.

The paper presents a stigmergic approach to engineer a guiding system to facilitate the complex problem of designing the group decision processes. The system aims to provide contextual, actionable recommendations based on the knowledge and past experience of its users as recorded in a collaborative working environment implemented around the concept of stigmergic systems. Through an agent-based socio-simulation experiment we have demonstrated already the feasibility of this approach. The paper illustrates how the simulation results are transferred into a guiding system that facilitates the group decision process design through iterative queries reformulations for the identification, representation and manipulation of the relevant knowledge.

Nowadays, most of the industrial companies adopt several digital tools to improve their performance, e.g. decreasing the production costs, reducing the delivery time, optimizing the production scheduling, etc.. However, the interoperability between such digital tools is still far from being reached, thus failing to fully exploit the potentiality of a virtual manufacturing approach. This research topic has been addressed by the European project named Virtual Factory Framework (VFF). This paper briefly introduces VFF and then demonstrates its potentiality by showing how it can be applied to an industrial case provided by the COMPA Company. Different software tools (i.e. a 3D visualization tool, a web portal, a Decision Support System, and a Failure Mode and Effects Analysis tool) have been integrated in the framework of VFF and then used to support the design of a manufacturing system and its production processes.

This paper describes iDecisionSupport, a collaborative decision-making support system that is characterized by and provides safety, usefulness, efficiency and usability. Its development is based on the principles of Decision Support Systems and is designed as a framework that can integrate third party applications as decision support tools. Routine procedures are facilitated by software agents and an internal workflow engine, while there is the advantage that the system can be accessed from anywhere at any time through a friendly web-interface.

The paper investigates how the engineered capabilities of structuring the knowledge encoded in collaborative workspaces affect the collective intelligence of its users. The investigation is made for the particular case of collaborative planning and is grounded on the theoretical framework of stigmergic systems. The knowledge structure encoded in collaborative workspaces in the form of a conceptual hierarchical task network is analysed by building a multi-agent simulation to evaluate the performance of different planning strategies. The results show that different representational complexities of collaborative planning knowledge have a great impact over the collective intelligence when the users are interacting directly or indirectly.