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Recent years have defined the need to reduce gas emissions to fight climate change, and society's move to green energies is important to make responsible use of non-renewable energies. Therefore, it is now important to use technologies to optimize the use of actual energy sources. In this aspect, the Internet of Things (IoT) technology has had a great impact on society. Hence, this research work aims to use IoT technology and multi-agent systems to optimize the use of central heating installation in buildings. It is intended to improve the user's comfort, reduce the consumption of energy and reduce the financial costs. Therefore, a multi-agent system is proposed to collect data from sensors located in a smart-home and obtain the best action to perform in a central heating system. The decisions will be taken by an intelligent agent based on fuzzy logic. This technology will allow for generating the control action with a fuzzy controller. The results obtained show that the proposal improves the actual system in terms of users' comfort and financial and energy savings. [ABSTRACT FROM AUTHOR]

Manual music classification is a slow and costly process. Most recent works about music auto-classification such as genre or emotions make this process easier, but are focused on a single task. In this work, a music multi-classification platform is presented. This platform is based on multi-agent systems, allowing to distribute the extraction, classification, and service tasks among agents. The platform performs a musical genre and emotional classification and provides context information of songs from social networks such as Twitter and Last.fm. The methods chosen based on meta-classifiers to perform single-label and multi-label classification obtain great results. In the case of multi-label classification, better results are obtained than in other previous works. [ABSTRACT FROM AUTHOR]

The control of consumption in homes and workplaces is an increasingly important aspect if we consider the growing popularity of smart cities, the increasing use of renewable energies, and the policies of the European Union on using energy in an efficient and clean way. These factors make it necessary to have a system that is capable of predicting what devices are connected to an electrical network. For demand management, the system must also be able to control the power supply to these devices. To this end, we propose the use of a multiagent system that includes agents with advanced reasoning and learning capacities. More specifically, the agents incorporate a case-based reasoning system and machine learning techniques. Besides, the multiagent system includes agents that are specialized in the management of the data acquired and the electrical devices. The aim is to adjust the consumption of electricity in networks to the electrical demand, and this will be done by acting automatically on the detected devices. The proposed system provides promising results; it is capable of predicting what devices are connected to the power grid at a high success rate. The accuracy of the system makes it possible to act according to the device preferences established in the system. This allows for adjusting the consumption to the current demand situation, without the risk of important home appliances being switched off. [ABSTRACT FROM AUTHOR]

There has been continuous research in the energy distribution sector because of its huge impact on modern societies. Nonetheless, aerial high voltage power lines are still supported by old transmission towers which involve some serious risks. Those risks may be avoided with periodic and expensive reviews. The main objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. More specifically, the work is focused on reducing the number of periodic reviews of transmission towers to avoid step and touch potentials, which are very dangerous for humans. A virtual organization-based multi-agent system is proposed in conjunction with different artificial intelligence methods and algorithms. The developed system is able to propose a sample of transmission towers from a selected set to be reviewed. The system ensures that the whole set will have similar values without needing to review all the transmission towers. As a result of this work, a website application is provided to manage all the review processes and all the transmission towers of Spain. It allows the companies that review the transmission towers to initiate a new review process for a whole line or area, while the system indicates the transmission towers to review. The system is also able to recommend the best place to locate a new transmission tower or the best type of structure to use when a new transmission tower must be used. [ABSTRACT FROM AUTHOR]

This paper proposes a multi agent system that provides visualization and prediction tools for bike sharing systems (BSS). The presented multi-agent system includes an agent that performs data collection and cleaning processes, it is also capable of creating demand forecasting models for each bicycle station. Moreover, the architecture offers API (Application Programming Interface) services and provides a web application for visualization and forecasting. This work aims to make the system generic enough for it to be able to integrate data from different types of bike sharing systems. Thus, in future studies it will be possible to employ the proposed system in different types of bike sharing systems. This article contains a literature review, a section on the process of developing the system and the built-in prediction models. Moreover, a case study which validates the proposed system by implementing it in a public bicycle sharing system in Salamanca, called SalenBici. It also includes an outline of the results and conclusions, a discussion on the challenges encountered in this domain, as well as possibilities for future work. [ABSTRACT FROM AUTHOR]

Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation. As novelty, this work presents a multi-agent architecture based on virtual organizations which allows to deploy a new embedded agent model in computationally limited autonomous sensors, making use of the Platform for Automatic coNstruction of orGanizations of intElligent Agents (PANGEA). To validate the proposed platform, different studies have been performed, where parameters specific to each animal are studied, such as physical activity, temperature, estrus cycle state and the moment in which the animal goes into labor. In addition, a set of applications that allow farmers to remotely monitor the livestock have been developed. [ABSTRACT FROM AUTHOR]

Nowadays, vehicles of modern fleets are endowed with advanced devices that allow the operators of a control center to have global knowledge about fleet status, including existing incidents. Fleet management systems support real-time decision making at the control center so as to maximize fleet performance. In this paper, setting out from our experience in dynamic coordination of fleet management systems, we focus on fleets that are open, dynamic and highly autonomous. Furthermore, we propose how to cope with the scalability problem as the number of vehicles grows. We present our proposed architecture for open fleet management systems and use the case of taxi services as example of our approach. We carried out some experiments, which showed our proposed algorithm outperform the most common assignment method both in waiting times of clients and taxi costs. [ABSTRACT FROM AUTHOR]

With the increase of intelligent systems based on Multi-Agent Systems (MAS) and the use of Wireless Sensor Networks (WSN) in context-aware scenarios, information fusion has become an essential part of this kind of systems where the information is distributed among nodes or agents. This paper presents a new MAS specially designed to manage data from WSNs, which was tested in a residential home for the elderly. The proposed MAS architecture is based on virtual organizations, and incorporates social behaviors to improve the information fusion processes. The data that the system manages and analyzes correspond to the actual data of the activities of a resident. Data is collected as the information event counts detected by the sensors in a specific time interval, typically one day. We have designed a system that improves the quality of life of dependant people, especially elderly, by fusioning data obtained by multiple sensors and information of their daily activities. The high development of systems that extract and store information make essential to improve the mechanisms to deal with the avalanche of context data. In our case, the MAS approach results appropriated because each agent can represent an autonomous entity with different capabilities and offering different services but collaborating among them. Several tests have been performed to evaluate this platform and preliminary results and the conclusions are presented in this paper. [ABSTRACT FROM AUTHOR]

The management of heterogeneous distributed sensor networks requires new solutions that can address the problem of automatically fusing the information coming from different sources in an efficient and effective manner. In the literature it is possible to find different types of data fusion and information fusion techniques in use today, but it is still a challenge to obtain systems that allow the automation or semiautomation of information processing and fusion. In this paper, we present a multiagent system that based on the organizational theory proposes a new model to automatically process and fuse information in heterogeneous distributed sensor networks. The proposed architecture is applied to a case study for indoor location where information is taken from different heterogeneous sensors. [ABSTRACT FROM AUTHOR]

This paper presents the THOMAS architecture, specially designed to model open multi-agent systems, and its application in the development of a multi-agent system for managing and planning surveillance routes for security personnel. THOMAS uses agents with reasoning and planning capabilities. These agents can perform a dynamic self-organization when they detect changes in the environment. THOMAS is appropriate for developing systems in highly dynamic environments similar to the one presented in this study, as demonstrated by the results obtained after having applied the system to a case study. [ABSTRACT FROM AUTHOR]

Abstract: When working in conjunction with multiagent systems, virtual organizations attempt to simulate the functions and interactions of entities in different environments. Recent studies have addressed the problem of assigning roles to agents that form part of the organization, and incorporating new agents to carry out certain tasks. However, these studies are limited to defining the norms and rules that determine the behavior of the organization. The present study proposes a virtual organization model for egovernment environments to assign resources and minimize the required personnel by forecasting workloads. To this end, a neural network, queuing theory, and CBR are used to obtain an efficient distribution. Queuing theory can establish the number of agents with a specific role that are necessary to maximize profits, while the network distributes roles among agents according to their respective efficiency. The final part of the paper is focused on validating the plan developed inside a case study centered on e-government in order to obtain empirical results. [Copyright &y& Elsevier]

Abstract: This paper presents a planning model integrated within a TB-CBP-BDI real-time intelligent agent that provides special abilities for planning in a predictable time, which makes its use especially appropriate in systems where certain temporal constraints must be satisfied. The proposed TB-CBP-BDI real-time agent is the core of a multi-agent system that manages security issues in industrial environments, where time constraints are a key factor. The proposed planning model facilitates the automatic temporal bounded reorganization of tasks to provide the system with adaptation abilities to the changes that occur in the environment. The planning mechanism focuses on optimizing industrial and manufacturing processes, specifically the tasks performed by the available security entities in these environments. Additionally, several Ambient Intelligence technologies such as QR-CODES, GPS, Wi-Fi and HSDPA are used to develop the intelligent environment that was tested and analyzed in this study. [Copyright &y& Elsevier]

Abstract: The use of architectures based on services and multi-agent systems has become an increasingly important part of the solution set used for the development of distributed systems. Nevertheless, these models pose a variety of problems with regards to security. This article presents the Adaptive Intrusion Detection Multi-agent System (AIDeMaS), a mechanism that has been designed to detect and block malicious SOAP messages within distributed systems built by service based architectures. AIDeMaS has been implemented as part of FUSION@, a multi-agent architecture that facilitates the integration of distributed services and applications to optimize the construction of highly-dynamic multi-agent systems. One of the main features of AIDeMaS is that is employs case-based reasoning mechanisms, which provide it with great learning and adaptation capabilities that can be used for classifying SOAP messages. This research presents a case study that uses the ALZ-MAS system, a multi-agent system built around FUSION@, in order to confirm the effectiveness of AIDeMaS. The preliminary results are presented in this paper. [Copyright &y& Elsevier]

Abstract: Security is a major concern when service environments are implemented. This has led to the proposal of a variety of specifications and proposals based on soft computing methods to provide the necessary security for these environments. However, most proposed approaches focus only on ensuring confidentiality and integrity, without putting forward mechanisms that ensure the availability of services and resources offered. A considerable number of attack mechanisms can lead to a web service system crash. As a result, the web service cannot allow access to authorized users. This type of attack is a so-called denial of service attack (DoS) which affects the availability of the services and recourses available. This article presents a novel soft computing-based approach to cope with DoS attacks, but unlike existing solutions, our proposal takes into account the different soft computing mechanisms that can lead to a DoS attack. Our approach is based on a real time classifier agent that incorporates a mixture of experts to choose a specific classification technique depending on the feature of the attack and the time available to solve the classification. With this scheme it is possible to divide the problem into subproblems, solving the classification of the web service requests in a more simple and effective way and always within a time bound interval. This research presents a case study to evaluate the effectiveness of the approach and also presents the preliminary results obtained with an initial prototype. [Copyright &y& Elsevier]

The European Union Establishes that for the next few years, a cleaner and more efficient energy system should be used. In order to achieve this, this work proposes an energy optimization method that facilitates the achievement of these objectives. Existing technologies allow us to create a system that optimizes the use of energy in homes and offers some type of benefit to its residents. Specifically, this study has developed a recommendation system based on a multiagent system that allows to obtain consumption data from electronic devices in a home, obtain information on electricity prices from the Internet, and provide recommendations based on consumption patterns of users and electricity prices. In this way, the system recommends new hours in which to use the appliances, offering the economic benefit that it would propose recommendations for the user. In this way, it is possible to distribute and optimize the use of energy in homes and reduce the peaks in electricity consumption. The system provides encouraging results in order to resolve the problem proposed by the European Union by optimizing the use of energy among different hours of the day and saving money for the customer. [ABSTRACT FROM AUTHOR]

People who suffer from any kind of motor difficulty face serious complications to autonomously move in their daily lives. However, a growing number research projects which propose different powered wheelchairs control systems are arising. Despite of the interest of the research community in the area, there is no platform that allows an easy integration of various control methods that make use of heterogeneous sensors and computationally demanding algorithms. In this work, an architecture based on virtual organizations of agents is proposed that makes use of a flexible and scalable communication protocol that allows the deployment of embedded agents in computationally limited devices. In order to validate the proper functioning of the proposed system, it has been integrated into a conventional wheelchair and a set of alternative control interfaces have been developed and deployed, including a portable electroencephalography system, a voice interface or as specifically designed smartphone application. A set of tests were conducted to test both the platform adequacy and the accuracy and ease of use of the proposed control systems yielding positive results that can be useful in further wheelchair interfaces design and implementation. [ABSTRACT FROM AUTHOR]

The early detection and monitoring of kidney disease continues being an important problem in medicine. The diagnosis and treatment of patients with this disease usually require expensive medical equipment that is difficult to install. Patients or medical centers may not always be able to afford such equipment. This work proposes the creation of a wireless sensor network for medical environments; it will assist medical professionals in the diagnosis and monitoring of patients with renal symptomatology. This work will focus on the analysis of symptoms that accompany this disease and the design of a system which will help determine types of kidney diseases. The proposed system will incorporate new hardware mechanisms and an intelligent system. It will be designed through a multi-agent architecture based on virtual organizations. This architecture will include a new model of agents, specifically designed to be incorporated into computationally limited devices. This hardware will be characterized by its low cost and ease of use. A case study has been carried out in order to validate the proposed architecture. In order to validate the proposed architecture, we designed a case study that aims to provide a technological tool for medical professionals and makes it possible to determine any diseases related to diuresis. The initial results are promising. [ABSTRACT FROM AUTHOR]

Abstract: Business Intelligence has gained relevance during the last years to improve business decision making. However, there is still a growing need of developing innovative tools that can help small to medium sized enterprises to predict risky situations and manage inefficient activities. This article present a multi-agent system especially created to detect risky situations and provide recommendations to the internal auditors of SMEs. The core of the multi-agent system is a type of agent with advanced capacities for reasoning to make predictions based on previous experiences. This agent type is used to implement a evaluator agent specialized in detect risky situations and an advisor agent aimed at providing decision support facilities. Both agents incorporate innovative techniques in the stages of the CBR system. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented. [Copyright &y& Elsevier]

Abstract: During the last years the use of Web Service-based applications has notably increased. However, the security has not evolved proportionally, which makes these applications vulnerable and objective of attacks. One of the most common attacks requiring novel solutions is the denial of service attack (DoS), caused for the modifications introduced in the XML of the SOAP messages. The specifications of existing security standards do not focus on this type of attack. This article presents the S-MAS architecture as a novel adaptive approach for dealing with DoS attacks in Web Service environments, which represents an alternative to the existing centralized solutions. S-MAS proposes a distributed hierarchical multi-agent architecture that implements a classification mechanism in two phases. The main benefits of the approach are the distributed capabilities of the multi-agent systems and the self-adaption ability to the changes that occur in the patterns of attack. A prototype of the architecture was developed and the results obtained are presented in this study. [ABSTRACT FROM AUTHOR]

• A distributed model predictive control with fuzzy negotiation has been developed. • The controller has been developed using a multi-agent software platform. • The fuzzy negotiation allows for the inclusion of economic or operating criteria. • The validation has been performed in a simulation of the four coupled tanks system. In this work, a multi-agent distributed model predictive control (DMPC) including fuzzy negotiation has been developed. A novel fuzzy inference system is introduced as a negotiation technique between agents in a cooperative game algorithm, allowing for the consideration of economic criteria and process constraints within the negotiation process, providing an easier interpretation of the available knowledge. The fuzzy negotiation produces smoother control actions than where the negotiation is based only on costs evaluation, because both agents provide their best to generate the final control action. The results show good tracking and disturbance rejection in the case study proposed. The methodology has been implemented in a JAVA based platform with a friendly user interface to deploy the multi-agent system (MAS), and it has been validated in the water level control in a four coupled tanks system. [ABSTRACT FROM AUTHOR]