PANGEA – Platform for Automatic coNstruction of orGanizations of intElligent Agents

Zato, Carolina; Villarrubia, Gabriel; Sánchez, Alejandro; Barri, Ignasi; Rubión, Edgar; Fernández, Alicia; Rebate, Carlos; Cabo, José A.; Álamos, Teresa; Muñuzuri, Jesús; Seco, Joaquín; Bajo, Javier; Corchado, Juan M.

doi:10.1007/978-3-642-28765-7_27

Cited by 60 publications

(74 citation statements)

References 18 publications

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“…The system is divided into the following groups of agents: bike sharing data agents, weather data collector agents, geographical information agents, data persistence agents, demand prediction agents and API agents. Several multi agent platforms such as SPADE [33,34], JADE [35], PANGEA [36,37], AIOMAS [38] and osBrain [39] were evaluated and osBrain was finally selected for this system because of its ease of use. Furthermore, it is implemented in Python (like SPADE and AIOMAS) and it is in continuous development nowadays.…”

Section: Proposed Systemmentioning

confidence: 99%

Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems

et al. 2018

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Featured Application: The main application of this work is the analysis and prediction of the demand in bike sharing systems using their open/private data. A multi agent system is proposed and a case study is conducted using the data of a bicycle sharing system from a middle size city.Abstract: 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.

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Section: Proposed Systemmentioning

confidence: 99%

Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems

et al. 2018

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“…A complete description of PANGEA can be found in [31]. The new architecture is organized in 4 layers as can be seen in Figure 1 and is developed according to the classification of the JDL fusion model [31,32]. The platform will facilitate the integration of sensing technologies, regardless of their nature, and will provide an openness environment that allows dynamic [10,[29][30][31].…”

Section: Proposed Architecturementioning

confidence: 99%

“…The new architecture is organized in 4 layers as can be seen in Figure 1 and is developed according to the classification of the JDL fusion model [31,32]. The platform will facilitate the integration of sensing technologies, regardless of their nature, and will provide an openness environment that allows dynamic [10,[29][30][31]. The process of obtaining data requires studying the technologies and existing communication protocols for sensor networks and defining a new broker and adapters to provide the platform with openness.…”

Section: Proposed Architecturementioning

confidence: 99%

Self-Organizing Architecture for Information Fusion in Distributed Sensor Networks

Bajo

Paz

Villarrubia

et al. 2015

International Journal of Distributed Sensor Networks

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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.

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“…From the perspective of this system, a VO-based MAS, PANGEA [19], has been used, which provides different tools to develop agents and deploy them in VO, and it is specially oriented to manage information obtained from the environment, including the information of multiple sensors. The characteristics of the agents systems allow this paradigm to be employed in a wide variety of research fields, such as data analysis in bioinformatics [20,21], classification of facial image classification according to gender and age [22], or WSA data fusion [18] but with a nexus that allows working with, and analyzing, large amounts of data.…”

Section: Agents and Information Fusionmentioning

confidence: 99%

Reuse of Waste Energy from Power Plants in Greenhouses through MAS‐Based Architecture

González‐Briones

Chamoso

Rodrı́guez

et al. 2018

Wireless Communications and Mobile Computing

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Today, most energy-intensive processes have a high degree of optimization. However, in some of these processes large amounts of energy are inevitably released due to the way in which this energy is used. One of the most obvious examples is produced in the power plants during the process of obtaining electrical energy through the transformation of some kind of energy (chemical, kinetic, thermal, lighting, and nuclear or solar energy, among others). This released energy can be used in other processes that may need it so that no additional energy is needed. One of the possible uses of this energy is its use in greenhouses. Greenhouses need large amounts of energy to recreate the climatic conditions that crops need, which are not those of the weather station. To take advantage of the energy released from the power stations in greenhouses, a system based on agents has been developed that manages energy and allows it to be reused. This paper explains how the system allows us to reuse energy by a power plant and how the agents that integrate the system by means of communication with sensors and actuators and the use of data analysis algorithms allow us to use this energy in greenhouses, providing a reduction of the energy they need without the system. The system has been tested in several greenhouses with a pepper crop.

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PANGEA – Platform for Automatic coNstruction of orGanizations of intElligent Agents

Cited by 60 publications

References 18 publications

Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems

Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems

Self-Organizing Architecture for Information Fusion in Distributed Sensor Networks

Reuse of Waste Energy from Power Plants in Greenhouses through MAS‐Based Architecture

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