Ambient Agents: Embedded Agents for Remote Control and Monitoring Using the PANGEA Platform

Villarrubia, Gabriel; Paz, Juan F. De; Bajo, Javier; Corchado, Juan M.

doi:10.3390/s140813955

Cited by 32 publications

(23 citation statements)

References 51 publications

(44 reference statements)

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“…PANGEA is an MAS framework focused on the development of virtual organizations of agents [23,24]. PANGEA is better than other multiagent platforms because it provides a number of agents that encapsulate elementary functionality, such as data access, service discovery [25] or rule control, and supports standard interagent communication protocols such as FIPA-ACL [26] PANGEA incorporates agents that manage security at the system level, unlike other types of systems in which it is necessary to develop these types of measures so that the information collected is really the one that is transmitted and analyzed [27].…”

Section: Mas Frameworkmentioning

confidence: 99%

Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

et al. 2018

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This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and their application to energy optimization problems. This methodology and related tools have contributed to changes in various paradigms used in energy optimization. Behavior and interactions between agents are key elements that must be understood in order to model energy optimization solutions that are robust, scalable and context-aware. The concept of MAS is introduced in this paper and it is compared with traditional approaches in the development of energy optimization solutions. The different types of agent-based architectures are described, the role played by the environment is analysed and we look at how MAS recognizes the characteristics of the environment to adapt to it. Moreover, it is discussed how MAS can be used as tools that simulate the results of different actions aimed at reducing energy consumption. Then, we look at MAS as a tool that makes it easy to model and simulate certain behaviors. This modeling and simulation is easily extrapolated to the energy field, and can even evolve further within this field by using the Internet of Things (IoT) paradigm. Therefore, we can argue that MAS is a widespread approach in the field of energy optimization and that it is commonly used due to its capacity for the communication, coordination, cooperation of agents and the robustness that this methodology gives in assigning different tasks to agents. Finally, this article considers how MASs can be used for various purposes, from capturing sensor data to decision-making. We propose some research perspectives on the development of electrical optimization solutions through their development using MASs. In conclusion, we argue that researchers in the field of energy optimization should use multi-agent systems at those junctures where it is necessary to model energy efficiency solutions that involve a wide range of factors, as well as context independence that they can achieve through the addition of new agents or agent organizations, enabling the development of energy-efficient solutions for smart cities and intelligent buildings.

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Section: Mas Frameworkmentioning

confidence: 99%

Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

et al. 2018

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“…Multisensor data fusion is a technology to enable combining information from several sources in order to form a unified picture [31]. Systems based on data fusion are now successfully exploited in various areas including sensor networks [32], image processing, and healthcare [33], where they demonstrate enhanced performance in terms of accuracy and reliability compared to single source based systems [34]. Modern healthcare systems commonly deploy data fusion algorithm to avoid intrinsic ambiguities caused by exploitation of unrelated type of sensors.…”

Section: Sensor Fusion In Fall Detectionmentioning

confidence: 99%

Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

2016

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Emergency situations associated with falls are a serious concern for an aging society. Yet following the recent development within ICT, a significant number of solutions have been proposed to track body movement and detect falls using various sensor technologies, thereby facilitating fall detection and in some cases prevention. A number of recent reviews on fall detection methods using ICT technologies have emerged in the literature and an increasingly popular approach considers combining information from several sensor sources to assess falls. The aim of this paper is to review in detail the subfield of fall detection techniques that explicitly considers the use of multisensor fusion based methods to assess and determine falls. The paper highlights key differences between the single sensor-based approach and a multifusion one. The paper also describes and categorizes the various systems used, provides information on the challenges of a multifusion approach, and finally discusses trends for future work.

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“…The server application is based on a virtual organization of agents. Virtual organizations can be considered an evolution of multi-agent architectures, which have been extensively explored as an alternative to develop context-aware systems [14]. This new perspective offers organizational norms, roles and the services associated with them.…”

Section: Wifi Module -Esp8266mentioning

confidence: 99%

“…The IoT device sends the data via WiFi connection to a Cloud service that monitors silo and feeds animals. A virtual organization of agents governs the system, where there are intelligent agents in sub-organizations dedicated to collect data, fuse information, control feeding, or active alarms in the case a risky situation is detected [6,7].…”

Section: Introductionmentioning

confidence: 99%

Smart feeding in farming through IoT in silos

Agrawal

Prieto

Ramos

et al. 2016

Advances in Intelligent Systems and Computing

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Smart farming practices are of utmost importance for any economy to foster its growth and development and tackle problems like hunger and food insecurity and ensure the well-being of its citizens. However, such practices usually require large investments that are not affordable for SMEs. Such is the case of expensive weighing machines for silos, while the range of possibilities of the Internet of Things (IoT) could intensively reduce these costs while connecting the data to intelligent Cloud services, such as smart feeding systems. The paper presents a novel IoT device and methodology to monitor quantity and quality of grains in silo by estimating the volume of grains at different time instants along with temperature and humidity in the silo. A smart feeding system, implemented via a virtual organization of agents, processes the data and regulates the grain provided to the animals. Experimental on-field measurements at a rabbit farm show the suitability of the proposed system to reduce waste as well as animal diseases and mortality.

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Ambient Agents: Embedded Agents for Remote Control and Monitoring Using the PANGEA Platform

Cited by 32 publications

References 51 publications

Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

Smart feeding in farming through IoT in silos

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