Advanced Architectures for Hybrid Edge Analytics Models on Adaptive Smart Areas

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 3085

Special Issue Editors

BISITE Research Group, University of Salamanca, Edificio Multiusos I+D+I, 37007 Salamanca, Spain
Interests: artificial intelligence; multi-agent systems; cloud computing and distributed systems; technology-enhanced learning
Special Issues, Collections and Topics in MDPI journals
Valencian Research Institute for Artificial Intelligence (VRAIn), Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
Interests: multi-agent systems; agreement technologies; ambient intelligence; affective computing; intelligent transport systems
Special Issues, Collections and Topics in MDPI journals
Centre for Intelligent Information Technologies (CETINIA), Universidad Rey Juan Carlos, Móstoles Campus, 28933 Mostoles, Spain
Interests: software systems; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

IoT and machine learning are two of the most exciting disciplines in technology today because of their profound impact on both businesses and individuals. Millions of small devices are already embedded in factories, cities, vehicles, phones, and our homes, collecting the information needed for intelligent decision making in areas such as industrial process optimization, predictive maintenance in buildings, people's mobility, home energy management, and more.

The focus of most of these applications is to gather information from the environment and transmit it over the Internet to powerful remote servers where intelligence and decision making resides. However, applications such as self-driving cars are critical and require accurate real-time responses.

To alleviate some of the above problems, edge computing has emerged, changing the way data is processed, improving response times, and addressing the connectivity, scalability, and security issues inherent to remote servers. Hybrid approaches have also emerged, with the goal of maximizing the benefits of edge and cloud.

All of these technologies are usually integrated in a hybrid architecture, which allows defined agents to perform the tasks assigned to them in a coordinated manner, each working independently and fulfilling the different needs that may arise without surveillance.

This Special Issue invites researchers to submit original quality studies regarding the technologies in the domains of IoT and machine learning, as well as their integration in hybrid architectures, and urges them to address the main subdisciplines, which include, but are not limited to, the following:

  • Edge computing;
  • Edge artificial intelligence;
  • Hybrid edge computing models;
  • Federated learning;
  • Machine and deep learning agent architectures;
  • Distributed problem solving;
  • Agent-based simulation;
  • Multi-agent systems (MAS);
  • Virtual agent organizations (VAO);
  • IoT and MAS;
  • IoT, smart cities, Industry 4.0;
  • Ambient intelligence.

Dr. Fernando De la Prieta Pintado
Dr. Vicente Julian Inglada
Prof. Dr. Sascha Ossowski
Dr. José Machado
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • edge computing
  • artificial intelligence
  • federated learning
  • multi-agent systems
  • IoT
  • ambient intelligence

Published Papers (3 papers)

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Research

18 pages, 1836 KiB  
Article
Robust Scheduling of Multi-Skilled Workforce Allocation: Job Rotation Approach
Electronics 2024, 13(2), 392; https://doi.org/10.3390/electronics13020392 - 17 Jan 2024
Viewed by 608
Abstract
This paper addresses scheduling challenges in software development organizations, specifically focusing on a novel version of the software project scheduling problem (SPSP). This enhanced model incorporates the dynamics of learning and forgetting phenomena, crucial in maintaining employee competencies, particularly when unexpected events such [...] Read more.
This paper addresses scheduling challenges in software development organizations, specifically focusing on a novel version of the software project scheduling problem (SPSP). This enhanced model incorporates the dynamics of learning and forgetting phenomena, crucial in maintaining employee competencies, particularly when unexpected events such as absenteeism or shifts in project priorities occur. The paper introduces a new declarative reference model for SPSP, aimed at proactively managing the assignment of versatile programmers to tasks within an portfolio of IT projects, while considering the effects of forgetting. Implemented within a constraints programming environment, this model facilitates decision making in project management for software companies. It serves to find feasible solutions and identify conditions necessary to meet specified expectations. The effectiveness of the proposed SPSP model is demonstrated through numerical examples. Full article
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29 pages, 2717 KiB  
Article
Emotional and Mental Nuances and Technological Approaches: Optimising Fact-Check Dissemination through Cognitive Reinforcement Technique
Electronics 2024, 13(1), 240; https://doi.org/10.3390/electronics13010240 - 04 Jan 2024
Viewed by 571
Abstract
The issue of the dissemination of fake news has been widely addressed in the literature, but the issue of the dissemination of fact checks to debunk fake news has not received sufficient attention. Fake news is tailored to reach a wide audience, a [...] Read more.
The issue of the dissemination of fake news has been widely addressed in the literature, but the issue of the dissemination of fact checks to debunk fake news has not received sufficient attention. Fake news is tailored to reach a wide audience, a concern that, as this paper shows, does not seem to be present in fact checking. As a result, fact checking, no matter how good it is, fails in its goal of debunking fake news for the general public. This paper addresses this problem with the aim of increasing the effectiveness of the fact checking of online social media posts through the use of cognitive tools, yet grounded in ethical principles. The paper consists of a profile of the prevalence of fact checking in online social media (both from the literature and from field data) and an assessment of the extent to which engagement can be increased by using simple cognitive enhancements in the text of the post. The focus is on Snopes and X (formerly Twitter). Full article
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20 pages, 11346 KiB  
Article
Towards Agrirobot Digital Twins: Agri-RO5—A Multi-Agent Architecture for Dynamic Fleet Simulation
Electronics 2024, 13(1), 80; https://doi.org/10.3390/electronics13010080 - 23 Dec 2023
Cited by 1 | Viewed by 697
Abstract
In this paper, we propose a multi-agent-based architecture for a Unity3D simulation of dynamic agrirobot-fleet-coordination methods. The architecture is based on a Robot Operating System (ROS) and Agrobots-SIM package that extends the existing package Patrolling SIM made for multi-robot patrolling. The Agrobots-SIM package [...] Read more.
In this paper, we propose a multi-agent-based architecture for a Unity3D simulation of dynamic agrirobot-fleet-coordination methods. The architecture is based on a Robot Operating System (ROS) and Agrobots-SIM package that extends the existing package Patrolling SIM made for multi-robot patrolling. The Agrobots-SIM package accommodates dynamic multi-robot task allocation and vehicle routing considering limited robot battery autonomy. Moreover, it accommodates the dynamic assignment of implements to robots for the execution of heterogeneous tasks. The system coordinates task assignment and vehicle routing in real time and responds to unforeseen contingencies during simulation considering dynamic updates of the data related to the environment, tasks, implements, and robots. Except for the ROS and Agrobots-SIM package, other crucial components of the architecture include SPADE3 middleware for developing and executing multi-agent decision making and the FIVE framework that allows us to seamlessly define the environment and incorporate the Agrobots-SIM algorithms to be validated into SPADE agents inhabiting such an environment. We compare the proposed simulation architecture with the conventional approach to 3D multi-robot simulation in Gazebo. The functioning of the simulation architecture is demonstrated in several use-case experiments. Even though resource consumption and community support are still an open challenge in Unity3D, the proposed Agri-RO5 architecture gives better results in terms of simulation realism and scalability. Full article
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