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- Collective intelligence in self-organized industrial cyber-physical systemsPublication . Sakurada, Lucas; Leitão, Paulo; Queiroz, JonasCyber-physical systems (CPS) play an important role in the implementation of new Industry 4.0 solutions, acting as the backbone infrastructure to host distributed intelligence capabilities and promote the collective intelligence that emerges from the interactions among individuals. This collective intelligence concept provides an alternative way to design complex systems with several benefits, such as modularity, flexibility, robustness, and reconfigurability to condition changes, but it also presents several challenges to be managed (e.g., non-linearity, self-organization, and myopia). With this in mind, this paper discusses the factors that characterize collective intelligence, particularly that associated with industrial CPS, analyzing the enabling concepts, technologies, and application sectors, and providing an illustrative example of its application in an automotive assembly line. The main contribution of the paper focuses on a comprehensive review and analysis of the main aspects, challenges, and research opportunities to be considered for implementing collective intelligence in industrial CPS. The identified challenges are clustered according to five different categories, namely decentralization, emergency, intelligent machines and products, infrastructures and methods, and human integration and ethics. Although the research indicates some potential benefits of using collective intelligence to achieve the desired levels of autonomy and dynamic adaptation of industrial CPS, such approaches are still in the early stages, with perspectives to increase in the coming years. Based on that, they need to be further developed considering some main aspects, for example, related to balancing the distribution of intelligence by the vertical and horizontal dimensions and controlling the nervousness in self-organized systems.
- Agent-based distributed data analysis in industrial cyber-physical systemsPublication . Queiroz, Jonas; Leitão, Paulo; Barbosa, José; Oliveira, Eugenio; Garcia, GiselaCyber-Physical System (CPS) is a key concept in the fourth industrial revolution, acting as the backbone infrastructure to develop Industry 4.0 compliant solutions based on decentralized networks of cyber-physical entities. In such systems, the distribution of intelligence and data analytics capabilities by different computational layers assumes a crucial relevance to support monitoring, diagnosis, prediction, and optimization tasks. Multiagent Systems (MAS) is a suitable approach to support this distribution through vertical and horizontal dimensions. In this context, this article introduces a modular agent-based architecture to balance the distribution of data analysis capabilities in industrial CPS. The proposed MAS solution was implemented in an industrial automotive factory plant, which applicability, novelty, and benefits were recognized, e.g., through its inclusion in the Innovation Radar of the Great EU-funded Innovations due to its contribution for the implementation of Zero Defects Manufacturing strategies in multistage production systems.
- A fuzzy logic recommendation system to support the design of cloud-edge data analysis in cyber-physical systemsPublication . Queiroz, Jonas; Leitão, Paulo; Oliveira, EugénioThe ongoing 4th industrial revolution is characterized by the digitization of industrial environments, mainly based on the use of Internet of Things, Cloud Computing and Artificial Intelligence (AI). Regarding AI, although data analysis has shown to be a key enabler of industrial Cyber-Physical Systems (CPS) in the development of smart machines and products, the traditional Cloud-centric solutions are not suitable to attend the data and time-sensitive requirements. Complementary to Cloud, Edge Computing has been adopted to enable the data processing capabilities at or close to the physical components. However, defining which data analysis tasks should be deployed on Cloud and Edge computational layers is not straightforward. This work proposes a framework to guide engineers during the design phase to determine the best way to distribute the data analysis capabilities among computational layers, contributing for a lesser ad-hoc design of distributed data analysis in industrial CPS. Besides defining the guidelines to identify the data analysis requirements, the core contribution relies on a Fuzzy Logic recommendation system for suggesting the most suitable layer to deploy a given data analysis task. The proposed approach is validated in a smart machine testbed that requires the implementation of different data analysis tasks for its operation.
- An agent-based industrial cyber-physical system deployed in an automobile multi-stage production systemPublication . Queiroz, Jonas; Leitão, Paulo; Barbosa, José; Oliveira, Eugénio; Garcia, GiselaIndustrial Cyber-Physical Systems (CPS) are promoting the development of smart machines and products, leading to the next generation of intelligent production systems. In this context, Artificial Intelligence (AI) is posed as a key enabler for the realization of CPS requirements, supporting the data analysis and the system dynamic adaptation. However, the centralized Cloud-based AI approaches are not suitable to handle many industrial scenarios, constrained by responsiveness and data sensitivity. Edge Computing can address the new challenges, enabling the decentralization of data analysis along the cyber-physical components. In this context, distributed AI approaches such as those based on Multi-agent Systems (MAS) are essential to handle the distribution and interaction of the components. Based on that, this work uses a MAS approach to design cyber-physical agents that can embed different data analysis capabilities, supporting the decentralization of intelligence. These concepts were applied to an industrial automobile multi-stage production system, where different kinds of data analysis were performed in autonomous and cooperative agents disposed along Edge, Fog and Cloud computing layers. © 2020, Springer Nature Switzerland AG.
- Ensino de robótica móvel através da realização de um hackathon em ROSPublication . Junior, Alexandre de Oliveira; Assumpção, Heitor Dutra; Queiroz, Jonas; Piadi, Luis; Leitão, Paulo; Pérez-Pons, María-Eugenia; Prieto, Javier; Parra-Domínguez, JavierA robótica móvel é um campo que vem crescendo constantemente nos últimos anos, possuindo aplicações em diversas áreas como a indústria, agricultura, medicina, entre outros. Sendo o ROS uma das principais plataformas de desenvolvimento de softwares desta área e visando a disseminação do conhecimento destas tecnologias, foi proposto um hackathon para fomentar a aprendizagem em ROS e robótica móvel. A decisão por essa abordagem foi devido à dificuldade de novos usuários no primeiro contato com a plataforma, por possuir conceitos complexos e ausência de front-end, o primeiro contato com ROS é difícil, levando os novos usuários a desistência. Com isso, o ensino foi feito por meio deste evento que é uma atividade imersiva e intensa para a solução de problemas na instância tecnólogica, principalmente em programação. De forma, que as primeiras barreiras fossem quebradas, o processo de aprendizagem facilitado e estimulasse os participantes a seguirem essa linha de pesquisa. O público alvo são estudantes de engenharia eletrotécnica, computação, mecânica e entusiastas em robótica. Neste paper será apresentada a estruturação do Hackathon, que compreende um nivelamento dos estudantes, para capacitá-los a programar as funcionalidades essenciais de um robô móvel e, por fim, o desafio robótico proposto. As etapas iniciais foram elaboradas com dificuldades que aumentaram progressivamente, iniciando com tarefas de controlo básico de um robô simulado até o desafio de desenvolver uma navegação autónoma em um ambiente de simulação buscando uma fonte de gás cuja posição é desconhecida.
- Learning cybersecurity in iot-based applications through a capture the flag competitionPublication . Junior, Alexandre Oliveira; Funchal, Gustavo Silva; Queiroz, Jonas; Loureiro, Jorge; Pedrosa, Tiago; Parra, Javier; Leitão, PauloThe Internet of Things (IoT) is one of the main foundations of Industry 4.0, providing widespread connectivity of systems and devices, which promotes significant benefits, such as improved performance, responsiveness, and reconfigurability. However, it also brings some security problems, which make these devices and systems vulnerable to cyberattacks, consequently demanding efficient learning and training initiatives to address the challenges regarding the qualification of undergraduate students and active professionals to design more secure systems, as well as to be more aware of cyberthreats during the management and use of them. With this in mind, this paper describes a Capture the Flag competition based on IoT cybersecurity. The participants’ feedback and performance evaluation show that this type of hands-on competition strongly contributes to learning the importance of cybersecurity in IoT-based applications.
- Hands-on learning modules for upskilling in industry 4.0 technologiesPublication . Oliveira Júnior, Alexandre de; Assumpção, Heitor Dutra; Queiroz, Jonas; Piardi, Luis; Parra, Javier; Leitão, PauloThe Industry 4.0 (I4.0) advent is re-shaping the way systems and processes operate by considering Cyber- Physical Systems combined with a plethora of emergent Information and Communication Technologies (ICT), e.g., Internet of Things (IoT), Artificial Intelligence, Cloud Computing and Intelligent Robotics. However, the emergence of such disruptive technologies strongly establishes a demand for upskilling and requalification of active professionals and young undergraduate students. This means that the wide adoption of the 14.0 systems and related tech-nologies is dependent on the efficient implementation of lifelong learning and training initiatives that address these challenges. Having this in mind, this paper describes the implementation of a series of short learning modules and hackathons that relies on a strong hands-on practical experimentation, regarding the upskilling in emergent ICT technologies, particularly focusing on IoT, mobile robotics and Multi-agent Systems. The preliminary efforts contributed to qualify undergraduate students and active professionals in disruptive ICT, with the attendees' feedback illustrating the importance of these kind of short and hands-on learning modules to address towards the continuous demands associated to the diaital transformation.
- A fuzzy logic approach for self-managing energy efficiency in IoT nodesPublication . Melo, Victória; Funchal, Gustavo Silva; Queiroz, Jonas; Leitão, PauloThe collection and analysis of data assume a crucial importance in the digital transformation era. Internet of Things (IoT) technologies allow to gather data from heterogeneous sources and make them available for data-driven systems aiming, e.g., monitoring, diagnosis, prediction and optimization. Several applications require that these IoT nodes be located remotely without connection to the electrical grid and being powered by batteries or renewable sources, thus requiring a more efficient management of the energy consumption in their operation. This paper aims to study and develop intelligent IoT nodes that embed Artificial Intelligence techniques to optimize their operation in terms of energy consumption when operating in constrained environments and powered by energy harvesting systems. For this purpose, a Fuzzy Logic system is proposed to determine the optimal operation strategy, considering the node’s current resource demands, the current battery condition and the power charge expectation. The proposed approach was implemented in IoT nodes measuring environmental parameters and placed in a university campus with Wi-Fi coverage. The achieved results show the advantage of adjusting the operation mode taking into consideration the battery level and the weather forecasts to increase the energy efficiency without compromising the IoT nodes’ functionalities and QoS.
- Agent-based data analysis towards the dynamic adaptation of industrial automation processesPublication . Queiroz, Jonas; Leitão, PauloIndustrial complex systems demand the dynamic adaptation and optimization of their operation to cope with operational and business changes. In order to address such requirements and challenges, cyber-physical systems promotes the development of intelligent production units and products. The realization of such concepts requires, amongst others, advanced data analysis approaches, capable to take advantage of increased availability of data, in order to overcome the inherent dynamics of industrial environments, by providing more modular, adaptable and responsiveness systems. In this context, this work introduces an agent-based data analysis approach to support the supervisory and control levels of industrial processes. It proposes to endow agents with data analysis capabilities and cooperation strategies, enabling them to perform distributed data analysis and dynamically improve their analysis capabilities, based on the aggregation of shared knowledge. Some experiments have been performed in the context of an electric micro grid to validate this approach.
- Smart inspection tools combining multi-agent systems and advanced quality controlPublication . Barbosa, José; Leitão, Paulo; Ferreira, Adriano; Queiroz, Jonas; Angione, Giacomo; Lo Duca, GiuliaAlthough the everlasting goal of achieving a zerodefect production system is not new, the current state of the art has not yet allowed to reach this objective. This paper describes the architectural system foundations of the European R&D GO0DMAN project where a multi-agent system is developed as the mean to provide a real-time, multi-level and multi-stage approach to reach a zero-defect production system in multi-stage environments. Particularly, the paper focuses the integration of software agents and quality control stations forming smart inspection tools, aligned with the cyber-physical systems principles. The proposed approach is validated using an electrical motor testbed, where the agent-based system allows the digitization of the running testing system in a multi-stage schema.
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