NaRALap: augmented reality system for navigation in laparoscopic surgery

The final publication is available at Springer via http://dx.doi.org/10.1007/s11548-011-0579-z.The AR system has a good resolution and currently is used for the placement of the trocars. Possible improvements will be performed to make the system independent of the camera position or to use natural marks. The biomechanical model and the AR algorithms will be combined with a tracker, for tracking the surgical instruments, in order to implement a valid system for liver biopsies. It will take into account the deformation due to the pneumoperitoneum and due to the breath of the patient. To develop the navigator that will guide the laparoscopic interventions, both AR system and biomechanical model will be combined with the laparoscopic camera in order to make an easier environment with only one vision in a 2D monitor.This work has been supported by the project MITYC (ref. TSI020100-2009-189). We would like to express our deep gratitude to the Hospital Clínica Benidorm for its participation in this project.López-Mir, F.; Martínez Martínez, F.; Fuertes Cebrián, JJ.; Lago, MA.; Rupérez Moreno, MJ.; Naranjo Ornedo, V.; Monserrat Aranda, C. (2011). NaRALap: augmented reality system for navigation in laparoscopic surgery. International Journal of Computer Assisted Radiology and Surgery. 6:98-99. https://doi.org/10.0.3.239/s11548-011-0579-zS9899

An Approach to Develop Digital Twins in Industry

[EN] The industry is currently undergoing a digital revolution driven by the integration of several enabling technologies. These include automation, robotics, cloud computing, industrial cybersecurity, systems integration, digital twins, etc. Of particular note is the increasing use of digital twins, which offer significant added value by providing realistic and fully functional process simulations. This paper proposes an approach for developing digital twins in industrial environments. The novelty lies in not only focusing on obtaining the model of the industrial system and integrating virtual reality and/or augmented reality but also in emphasizing the importance of incorporating other enabled technologies of Industry 4.0, such as system integration, connectivity with standard and specific industrial protocols, cloud services, or new industrial automation systems, to enhance the capabilities of the digital twin. Furthermore, a proposal of the software tools that can be used to achieve this incorporation is made. Unity is chosen as the real-time 3D development tool for its cross-platform capability and streamlined industrial system modeling. The integration of augmented reality is facilitated by the Vuforia SDK. Node-RED is selected as the system integration option, and communications are carried out with MQTT protocol. Finally, cloud-based services are recommended for effective data storage and processing. Furthermore, this approach has been used to develop a digital twin of a robotic electro-pneumatic cell.SIGrant PID2020-117890RB-I00 funded by MCIN/AEI/10.13039/501100011033. The work of José Ramón Rodríguez-Ossorio and Guzmán González-Mateos has been supported by grants from the Research Program of the University of León.Agencia Estatal de Investigació

Guidelines to develop demonstration models on industry 4.0 for engineering training

[EN] Industrial digitization is currently a great challenge which involves continuous advances in tech-nologies such as automation, robotics, internet of things, cloud computing, big data, virtual and augmented reality or cybersecurity. Only those companies able to adapt and with qualified work-ers will be competitive. Therefore, it is necessary to design new environments to train students and workers in these enabling technologies. In this paper, a set of guidelines is proposed to develop a demonstration model on Industry 4.0. Following these guidelines, an existing manufacturing industrial system, based on an electro-pneumatic cell for classifying pieces, is updated to the Industry 4.0 paradigm. The result is an Industry 4.0 demonstration model where enabling tech-nologies are added in an integrated way. In this manner, students do not only train in each technology, but also understand the interactions between them. In the academic year 2020/21, this demonstration model has been used by engineering students in a subject of a master’s degree. Impressions and comments from students about the structure and management of the environ-ment, as well as the influence on their learning process are collected and discussed.SIThis work was supported by the Spanish State Research Agency, MCIN/AEI/10.13039/501100011033 under Grant PID2020-117890RB-I00. The work of José Ramón Rodríguez- Ossorio was supported by a grant of the Research Programme of the Universidad de León 2020. The work of Guzmán González-Mateos was supported by a grant of the Research Programme of the University of León 202

Hands-on training in industrial cybersecurity for a multidisciplinary Master's degree

[EN] As a response to the scarcity of workforce with essential competences for Industry 4.0, academic institutions are making an effort to propose specialized educational programs. In this context of digitalization, industrial cybersecurity is an increasingly important aspect. Nevertheless, industrial cybersecurity is a challenging topic that requires the understanding of both information technologies and the operation of industrial facilities. Furthermore, practical training requires realistic environments to be useful. For this reason, in this work, we present a hands-on activity on a remotely accessible training platform to complement the theoretical concepts of a Master's degree course that deals with the introduction to industrial cybersecurity. This platform presents the students a realistic automation environment with industrial hardware and software. The educational experience has been assessed with regard to the students’ perception and its technical operation. The platform was found useful for learning and motivating, although the perceived degree of difficulty needs to be adjust to promote students’ self-confidence.SIThis work is the result of collaboration between the SUPPRESS research group and Schneider Electric, through the framework agreement between Schneider Electric and the Universidad de León.The work of José Ramón Rodríguez-Ossorio was supported by a grant of the Research Programme of the University of León 2020.The work of Guzmán González-Mateos was supported by a grant of the Research Programme of the University of León 2021

Environment for Education on Industry 4.0

[EN] A new industrial production model based on digitalization, system interconnection, virtualization and data exploitation, has emerged. Upgrade of production processes towards this Industry 4.0 model is one of the critical challenges for the industrial sector and, consequently, the training of students and professionals has to address these new demands. To carry out this task, it is essential to develop educational tools that allow students to interact with real equipment that implements, in an integrated way, new enabling technologies, such as connectivity with standard protocols, storage and data processing in the cloud, machine learning, digital twins and industrial cybersecurity measures. For that reason, in this work, we present an educational environment on Industry 4.0 that incorporates these technologies reproducing realistic industrial conditions. This environment includes cutting-edge industrial control system technologies, such as an industrial firewall and a virtual private network (VPN) to strengthen cybersecurity, an Industrial Internet of Things (IIoT) gateway to transfer process information to the cloud, where it can be stored and analyzed, and a digital twin that virtually reproduces the system. A set of hands-on tasks for an introductory automation course have been proposed, so that students acquire a practical understanding of the enabling technologies of Industry 4.0 and of its function in a real automation. This course has been taught in a master’s degree and students have assessed its usefulness by means of an anonymous survey. The results of the educational experience have been useful both from the students’ and faculty’s viewpoint.SIAgencia estatal de investigación MCIN/AEI/ 10.13039/501100011033Comité español de Automática y Siemens a través del premio ‘Automatización y Digitalización. Industria 4.0

Cybersecurity training in control systems using real equipment

[EN] The relevance of cybersecurity in the field of critical infrastructures has been reinforced in the last years, as a result of the increased number of incidents. The European Union has developed policies oriented to promote research and education in security and critical infrastructure protection. It is widely recognized that there is a shortage of qualified cybersecurity professionals due to the increasing demand. The situation is even more serious in the area of cybersecurity of critical infrastructures, due to the special characteristics of the control and monitoring systems needed for their operation. Furthermore, there is a knowledge gap between the industrial control experts, who generally have not received training in computer security, and the cybersecurity experts, who ignore the operation of industrial control systems. It is therefore necessary to create educational environments that support training and research oriented to bridge this gap without. For that reason, this paper presents a Laboratory of Critical Infrastructures Cybersecurity (CICLab) that is flexible enough to create different settings that simulate real situations on the critical infrastructure control systems. For that purpose, the laboratory includes different field, control and monitoring technologies that are widely used in four sectors: industry, energy management, building management and smart cities. Some educational activities are presented in the framework of this laboratory.SI2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

Remote training in cybersecurity for industrial control systems

[EN] Cybersecurity is a key subject for digital transformation where institutional, industrial and educational sectors should be involved in a coordinated way. Currently, there is a lack of workforce with essential competences to apply secure solutions in an industrial environment. For that reason, in order to address this increasing demand, universities promote industrial cybersecurity courses and related programs. But training of future cybersecurity professionals in the industrial sector requires appropriate frameworks that facilitate teaching students a range of evolving technologies. In this work, a platform for remote training in cybersecurity is proposed using cabinets that include specific elements for automation and control as well as additional resources for administration and communication tasks. The platform allowed the development of two cybersecurity courses whose students were asked for feedback about the structure of the laboratory, its operation and also the learning process. The results show a wide acceptance of the platform used in the course and an improvement of students’ motivation in the subject.SIThis work is the result of collaboration between the SUPPRESS research group and Schneider Electric, established through the framework agreement between Schneider Electric and the Universidad de Le´on

Virtual sensor for probabilistic estimation of the evaporation in cooling towers

16th AIAI (Artificial Intelligence Applications and Innovations) Joint International Conference[EN] Global natural resources are affected by several causes such as climate change effects or unsustainable management strategies. Indeed, the use of water has been intensified in urban buildings because of the proliferation of HVAC (Heating, Ventilating and Air Conditioning) systems, for instance cooling towers, where an abundant amount of water is lost during the evaporation process. The measurement of the evaporation is challenging, so a virtual sensor could be used to tackle it, allowing to monitor and manage the water consumption in different scenarios and helping to plan efficient operation strategies which reduce the use of fresh water. In this paper, a deep generative approach is proposed for developing a virtual sensor for probabilistic estimation of the evaporation in cooling towers, given the surrounding conditions. It is based on a conditioned generative adversarial network (cGAN), whose generator includes a recurrent layer (GRU) that models the temporal information by learning from previous states and a densely connected layer that models the fluctuations of the conditions. The proposed deep generative approach is not only able to yield the estimated evaporation value but it also produces a whole probability distribution, considering any operating scenario, so it is possible to know the confidence interval in which the estimation is likely found. This deep generative approach is assessed and compared with other probabilistic state-of-the-art methods according to several metrics (CRPS, MAPE and RMSE) and using real data from a cooling tower located at a hospital building. The results obtained show that, to the best of our knowledge, our proposal is a noteworthy method to develop a virtual sensor, taking as input the current and last samples, since it provides an accurate estimation of the evaporation with wide enough confidence intervals, contemplating potential fluctuations of the conditions.S

Probabilistic Estimation of Evaporated Water in Cooling Towers Using a Generative Adversarial Network

[EN] Water is a critical resource for life on the earth but it is becoming increasingly scarce. Therefore, water use should be sustainable and properly managed. The problem of water scarcity is still more stressed in cities, where buildings consume more and more water, especially commercial and institutional ones. In those buildings, HVAC (Heating, Ventilating and Air Conditioning) systems make an intensive use of water, especially the water-based cooling systems such as cooling towers, where a large amount of water is evaporated. In this paper, a method is proposed in order to estimate the evaporated water in cooling towers, considering the variations of environmental and operating conditions. We propose the use of a generative model which is able to generalize the estimation of the evaporated water, even in situations not included in the training data. A generative adversarial network (GAN) is used for training a deep learning-based generative model. The proposed method is tested using real data from a cooling tower located at the Hospital of Le´on. Results show the probability distribution within which the estimation of evaporated water can be found, given the environmental and operating conditions.S

Using Low-Cost Open Source Hardware To Control Puma560 Motors

[EN] In this paper, we present a low-cost approach to upgrade an outdated PUMA (Programmable Universal Machine for Assembly) 560 robot in order to widen the number and type of possible hands-on experiments in control and instrumentation education. Another aim of the upgrade is to enable its future connection to a remote laboratory. We propose a scalable structure to control and monitoring PUMA560 motors. This approach combines several different technologies: A Raspberry Pi for control and monitoring, Python to control the system and chart data, as well as converters and drivers with serial I2C bus interface connectivity to read/write data from/to Puma560 robot. The ideas here explained could be applicable to other physical systems with similar characteristics and number of variables.S