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Advances in Agents and Multiagent Systems for Sensor Applications
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Advances in Agents and Multiagent Systems for Sensor Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3046

Special Issue Editors

Dr. Fernando De la Prieta Pintado

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Guest Editor
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
Dr. Sara Rodriguez

E-Mail Website
Guest Editor
BISITE Research Group, University of Salamanca, 37008 Salamanca, Spain
Interests: artificial intelligence; distributed computing; machine learning; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Juan M. Corchado

E-Mail Website
Guest Editor
1. BISITE Research Group, University of Salamanca, 37007 Salamanca, Spain
2. Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain
3. Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan
Interests: artificial intelligence; smart cities; smart grids
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Vicent Botti

E-Mail Website
Guest Editor
VRAIN Valencian Research Institute for Artificial Intelligence, Universitat Politècnica de València, 46022 València, Spain
Interests: affective computing; agreement technology; artificial intelligence; computational chemistry; computer science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Research on intelligent distributed systems has matured within the last decade and many effective applications are now being deployed. Technologies in distributed environments, such as multi-agent systems, the Internet of Things (IoT), wireless devices, Industry 4.0, etc. are increasing and are becoming an element of high added value and economic potential, both in industrial and research fields.

Most computing systems from personal laptops/computers to cluster/grid/cloud computing systems are available for parallel and distributed computing. Distributed computing performs an increasingly important role in modern signal/data processing, information fusion and electronics engineering (e.g., electronic commerce, mobile communications and wireless devices). Particularly, applying multi-agent systems in distributed environments is becoming an element of high added value and economic potential.

This Special Issue aims to advance the state-of-the-art application of intelligent methods to improve distributed scenarios, with a special focus on those applications that take practical applications of multi-Agent Systems, human collaboration, interactions, communication, or industrial scenarios into consideration. We especially encourage the submission of articles describing applications, but we also welcome theoretical work and review articles on novel applications of multi-agent systems and intelligent methods to distributed environments communications such as the Internet of Things (IoT), electronic commerce, mobile communications and wireless devices. 

Topics of interest include, but are not limited to practical applications of: 

  • Multi-agent Systems 
  • Distributed problem solving
  • Agent cooperation and negotiation
  • Human agent interaction, social networks, virtual communities
  • Reputation, trust, privacy and security
  • Agent engineering and development tools
  • Internet of Things, sensors and actuators
  • Big data and machine learning
  • Smart cities, smart homes, smart buildings, smart health, smart mobility and transportation
  • Semantic web, linked data
  • Agent-based simulation and prediction, social simulation

You may choose our Joint Special Issue in Robotics, or Joint Special Issue in Systems.

Dr. Fernando De la Prieta
Dr. Sara Rodriguez
Prof. Dr. Juan M. Corchado
Prof. Dr. Vicent Botti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

18 pages, 7305 KiB  
Article
HyPedSim: A Multi-Level Crowd-Simulation Framework—Methodology, Calibration, and Validation
by Huu-Tu Dang, Benoit Gaudou and Nicolas Verstaevel
Sensors 2024, 24(5), 1639; https://doi.org/10.3390/s24051639 - 02 Mar 2024
Viewed by 438
Abstract
Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas [...] Read more.
Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based model to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a use case of pedestrians at the Festival of Lights, Lyon, France. Pedestrian outflow data are extracted from video recordings of exiting crowds at the festival. The hybrid model is calibrated and validated using a genetic algorithm that optimises the match between simulated and observed outflow data. Additionally, a local sensitivity analysis is then conducted to identify the most sensitive parameters in the model. Finally, the performance of the hybrid model is compared to different models in terms of density map and computation time. The results demonstrate that the hybrid model has the capacity to effectively simulate pedestrians across varied density scenarios while optimising computational performance compared to other models. Full article
(This article belongs to the Special Issue Advances in Agents and Multiagent Systems for Sensor Applications)
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23 pages, 3301 KiB  
Article
Extending the Framework for Developing Intelligent Virtual Environments (FIVE) with Artifacts for Modeling Internet of Things Devices and a New Decentralized Federated Learning Based on Consensus for Dynamic Networks
by Miguel Rebollo, Jaime Andrés Rincon, Luís Hernández, Francisco Enguix and Carlos Carrascosa
Sensors 2024, 24(4), 1342; https://doi.org/10.3390/s24041342 - 19 Feb 2024
Viewed by 561
Abstract
One of the main lines of research in distributed learning in recent years is the one related to Federated Learning (FL). In this work, a decentralized Federated Learning algorithm based on consensus (CoL) is applied to Wireless Ad-hoc Networks (WANETs), where the agents [...] Read more.
One of the main lines of research in distributed learning in recent years is the one related to Federated Learning (FL). In this work, a decentralized Federated Learning algorithm based on consensus (CoL) is applied to Wireless Ad-hoc Networks (WANETs), where the agents communicate with other agents to share their learning model as they are available to the wireless connection range. When deploying a set of agents, it is essential to study whether all the WANET agents will be reachable before the deployment. The paper proposes to explore it by generating a simulation close to the real world using a framework (FIVE) that allows the easy development and modification of simulations based on Unity and SPADE agents. A fruit orchard with autonomous tractors is presented as a case study. The paper also presents how and why the concept of artifact has been included in the above-mentioned framework as a way to highlight the importance of some devices used in the environment that have to be located in specific places to ensure the full connection of the system. This inclusion is the first step to allow Digital Twins to be modeled with this framework, now allowing a Digital Shadow of those devices. Full article
(This article belongs to the Special Issue Advances in Agents and Multiagent Systems for Sensor Applications)
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