This paper introduces wireless sensor networks for Ambient Assisted Living as a proof of concept. Our workgroup has developed an arrhythmia detection algorithm that we evaluate in a closed space using a wireless sensor network to relay the information collected to where the information can be registered, monitored and analyzed to support medical decisions by healthcare providers. The prototype we developed is then evaluated using the TelosB platform. The proposed architecture considers very specific restrictions regarding the use of wireless sensor networks in clinical situations. The seamless integration of the system architecture enables both mobile node and network configuration, thus providing the versatile and robust characteristics necessary for real-time applications in medical situations. Likewise, this system architecture efficiently permits the different components of our proposed platform to interact efficiently within the parameters of this study.
New applications of industrial automation request great flexibility in the systems, supported by the increase in the interconnection between its components, allowing access to all the information of the system and its reconfiguration based on the changes that occur during its operations, with the purpose of reaching optimum points of operation. These aspects promote the Smart Factory paradigm, integrating physical and digital systems to create smarts products and processes capable of transforming conventional value chains, forming the Cyber-Physical Systems (CPSs). This flexibility opens a large gap that affects the security of control systems since the new communication links can be used by people to generate attacks that produce risk in these applications. This is a recent problem in the control systems, which originally were centralized and later were implemented as interconnected systems through isolated networks. To protect these systems, strategies that have presented acceptable results in other environments, such as office environments, have been chosen. However, the characteristics of these applications are not the same, and the results achieved are not as expected. This problem has motivated several efforts in order to contribute from different approaches to increase the security of control systems. Based on the above, this work proposes an architecture based on artificial neural networks for detection and isolation of cyber attacks Denial of Service (DoS) and integrity in CPS. Simulation results of two test benches, the Secure Water Treatment (SWaT) dataset, and a tanks system, show the effectiveness of the proposal. Regarding the SWaT dataset, the scores obtained from the recall and F1 score metrics was 0.95 and was higher than other reported works, while, in terms of precision and accuracy, it obtained a score of 0.95 which is close to other proposed methods. With respect to the interconnected tank system, scores of 0.96,0.83,0.81, and 0.83 were obtained for the accuracy, precision, F1 score, and recall metrics, respectively. The high true negatives rate in both cases is noteworthy. In general terms, the proposal has a high effectiveness in detecting and locating the proposed attacks.
Industry 4.0 involves the digital transformation of the industry with the integration and digitization of all industrial processes that make up the value chain, which is characterized by adaptability, flexibility, and efficiency to meet the needs of customers in today's market. Therefore, the adaptations of the new bioprocess industry require a lot of flexibility to react quickly and constantly to market changes and to be able to offer more specialized, customized products with high operational efficiency. This paper presents a flexible, scalable, and robust framework based on software components, container technology, microservice concepts, and the publish/subscribe paradigm. This framework allows new components to be added or removed online, without the need for system reconfiguration, while maintaining temporal and functional constraints in industrial automation systems. The main objective of the framework proposed is the use of components based on microservices, allowing easy implementation, scalability, and fast maintenance, without losing or degrading the robustness from previous developments. Finally, the effectiveness of the proposed framework was verified in two case studies (1) a soursop soda making process is presented, with a fuzzy controller implemented to keep the pasteurizer output flow constant (UHT) and (2) an automatic storage tank selection and filling process with actuated valves to direct the fluid to the corresponding tank at the time to start the process. The results showed that the platform provided a high-fidelity design, analysis, and testing environment for the flow of cyber information and its effect on the physical operation in a beverage processing plant with high demand for flexibility, scalability, and robustness of its processes, as they were experimentally verified in a real production process.INDEX TERMS Industry 4.0, distributed industrial automation systems, interoperability, middleware, industrial cyber-physical systems.
Modern industries require constant adaptation to new trends. Thus, they seek greater flexibility and agility to cope with disruptions, as well as to solve needs or meet the demand for growth. Therefore, smart industrial applications require a lot of flexibility to be able to react more quickly to continuous market changes, offer more personalized products, increase operational efficiency, and achieve optimum operating points that integrate the entire value chain of a process. This requires the capture of new data that are subsequently processed at different levels of the hierarchy of automation processes, with requirements and technologies according to each level. The result is a new challenge related to the addition of new functionalities in the processes and the interoperability between them. This paper proposes a distributed computational component-based framework that integrates communication, computation, and storage resources and real-time capabilities through container technology, microservices, and the publish/subscribe paradigm, as well as contributing to the development and implementation of industrial automation applications by bridging the gap between generic architectures and physical realizations. The main idea is to enable plug-and-play software components, from predefined components with their interrelationships, to achieve industrial applications without losing or degrading the robustness from previous developments. This paper presents the process of design and implementation with the proposed framework through the implementation of a complex pH control process, ranging from the simulation part to its scaling and implementation to an industrial level, showing the plug-and-play assembly from a definition of components with their relationships to the implementation process with the respective technologies involved. The effectiveness of the proposed framework was experimentally verified in a real production process, showing that the results scaled to an industrial scale comply with the simulated design process. A qualitative comparison with traditional industrial implementations, based on the implementation requirements, was carried out. The implementation was developed in the beverage production plant “Punta Delicia”, located in Colima, Mexico. Finally, the results showed that the platform provided a high-fidelity design, analysis, and testing environment for cyber information flow and their effect on the physical operation of the pH control.
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