Percorrer por autor "Prieta, Fernando de la"
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- Distributed machine learning and multi-agent systems for enhanced attack detection and resilience in iot networksPublication . Funchal, Gustavo Silva; Pedrosa, Tiago; Prieta, Fernando de la; Leitão, PauloThe exponential growth of connected devices, including sensors, mobile devices, and various Internet of Things (IoT) devices, has resulted in a substantial increase in data generation. Traditionally, data analysis involves transferring data to cloud computing systems, leading to latency issues and excessive network traffic. Edge computing emerges as a promising solution by bringing processing closer to the data sources. However, edge computing faces challenges, particularly in terms of limited computational power, which can create constraints in the execution of machine learning (ML) tasks. This paper aims to analyze strategies for distributing ML tasks among multiple nodes based on multi-agent systems (MAS) technology to have a collaborative approach and compare these strategies to provide an overview of best practices for achieving the optimal performance in intrusion detection for Industrial Internet of Things (IIoT). In this way, the well-known CICIoT2023 data set was used, and centralized and distributed ML techniques were implemented, and evaluated. The distributed edge ML approach achieved promising results, presenting an improvement of between 7.73% and 32.18% in the correction of wrong predictions of detection of attacks on IoT devices, significantly improving the precision and recall of the applied techniques.
- In-depth analysis of organisational structures for digital twin ecosystemsPublication . Melo, Victória; Pires, Flávia; Barbosa, José; Prieta, Fernando de la; Leitão, PauloThe Digital Twin (DT) plays a crucial role in the digital transformation era by providing a bidirectional synchronized digital representation of an asset, capable of performing real-time monitoring, simulation, and data analysis. Generally, DTs are designed as single units following a centralised approach. However, this paradigm is evolving towards DT ecosystems, consisting of a network of multiple interconnected DTs. The benefits of such ecosystems depend on their intended purpose and application, which are strongly influenced by the design and structural configuration adopted during implementation. This paper aims to analyse different organisational structures, namely centralised, hierarchical, heterarchical, and holonic, for the design, development, and implementation of DT ecosystems, assessing their benefits and challenges across a set of aspects. A case study of a modular conveyor transfer system was used to test the different organisational structures, supporting the comparative analysis and the discussion of the research challenges related to this topic.
- Relationship of digital product passport and digital twin in industry 4.0 contextPublication . Melo, Victória; Prieta, Fernando de la; Leitão, PauloThe advances brought by Industry 4.0 contribute to the digital transformation and green transition, accelerating advances toward a circular economy. In this context, some interconnected concepts share similarities and complementarities, that can be analyzed to understand the potential benefits of their associated use. This paper discusses the relationship between the Digital Product Passport (DPP) and the Digital Twin concepts, highlighting their alignment and exploring their similarities and differences, aiming to understand how they complement each other. Therefore, the typology of assets, data model, and functionalities were analyzed, as well as an architectural and component alignment based on the elements provided by ISO 23247 while considering that the DPP concept is still in development. A case study is also presented to illustrate the implementation of both concepts.
- Ten years of asset administration shell: developments, research opportunities, and adoption challengesPublication . Sakurada, Lucas; Prieta, Fernando de la; Leitão, PauloOver the past decade, the Asset Administration Shell (AAS) has emerged as a cornerstone of digital transformation in Industry 4.0 (I4.0), providing a standardized approach to managing digital representations of industrial assets. With 2025 marking approximately ten years since its introduction, this article aims to provide a comprehensive analysis and discussion of AAS development over the past decade, potential research opportunities, and the challenges associated with its adoption. To this end, the study combines a literature survey with an examination of specifications from key organizations, such as the Plattform Industrie 4.0 and the Industrial Digital Twin Association (IDTA), which play a central role in the AAS standardization and development. A key insight from this survey is that AAS is progressing toward becoming a game-changer in realizing I4.0. Unlike a decade ago, AAS has now reached a level of maturity that enables its increasing adoption, supported by specifications and standards, dedicated development platforms for its implementation, and several examples in the literature showing a wide range of applications. Additionally, research opportunities for AAS align with emerging industrial trends and contribute to addressing them. However, several challenges must still be addressed to facilitate the widespread adoption of the AAS.