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683 results on '"Longhi, Sauro"'

7. The Overall Labour Effectiveness to Improve Competitiveness and Productivity in Human-Centered Manufacturing

Author

Bonci, Andrea, Stadnicka, Dorota, Longhi, Sauro, Cavas-Martínez, Francisco, Editorial Board Member, Chaari, Fakher, Series Editor, di Mare, Francesca, Editorial Board Member, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Editorial Board Member, Ivanov, Vitalii, Series Editor, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Kujawińska, Agnieszka, editor, Machado, Jose, editor, and Pavlenko, Ivan, editor

Published
2022
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9. Human-in-the-Loop Approach to Safe Navigation of a Smart Wheelchair via Brain Computer Interface

Author

Ciabattoni, Lucio, Ferracuti, Francesco, Freddi, Alessandro, Iarlori, Sabrina, Longhi, Sauro, Monteriù, Andrea, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Monteriù, Andrea, editor, Freddi, Alessandro, editor, and Longhi, Sauro, editor

Published
2021
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11. DeepESN Neural Networks for Industrial Predictive Maintenance through Anomaly Detection from Production Energy Data.

Author

Bonci, Andrea, Fredianelli, Luca, Kermenov, Renat, Longarini, Lorenzo, Longhi, Sauro, Pompei, Geremia, Prist, Mariorosario, and Verdini, Carlo

Subjects
INDUSTRIAL energy consumption, ANOMALY detection (Computer security), ARTIFICIAL intelligence, SMART meters, TIME series analysis
Abstract

Optimizing energy consumption is an important aspect of industrial competitiveness, as it directly impacts operational efficiency, cost reduction, and sustainability goals. In this context, anomaly detection (AD) becomes a valuable methodology, as it supports maintenance activities in the manufacturing sector, allowing for early intervention to prevent energy waste and maintain optimal performance. Here, an AD-based method is proposed and studied to support energy-saving predictive maintenance of production lines using time series acquired directly from the field. This paper proposes a deep echo state network (DeepESN)-based method for anomaly detection by analyzing energy consumption data sets from production lines. Compared with traditional prediction methods, such as recurrent neural networks with long short-term memory (LSTM), although both models show similar time series trends, the DeepESN-based method studied here appears to have some advantages, such as timelier error detection and higher prediction accuracy. In addition, the DeepESN-based method has been shown to be more accurate in predicting the occurrence of failure. The proposed solution has been extensively tested in a real-world pilot case consisting of an automated metal filter production line equipped with industrial smart meters to acquire energy data during production phases; the time series, composed of 88 variables associated with energy parameters, was then processed using the techniques introduced earlier. The results show that our method enables earlier error detection and achieves higher prediction accuracy when running on an edge device. [ABSTRACT FROM AUTHOR]

Published
2024
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12. An Echo State Network-Based Light Framework for Online Anomaly Detection: An Approach to Using AI at the Edge.

Author

Bonci, Andrea, Kermenov, Renat, Longarini, Lorenzo, Longhi, Sauro, Pompei, Geremia, Prist, Mariorosario, and Verdini, Carlo

Subjects
ARTIFICIAL neural networks, ARTIFICIAL intelligence, ANOMALY detection (Computer security), INDUSTRIAL safety, EDGE computing
Abstract

Production efficiency is used to determine the best conditions for manufacturing goods at the lowest possible unit cost. When achieved, production efficiency leads to increased revenues for the manufacturer, enhanced employee safety, and a satisfied customer base. Production efficiency not only measures the amount of resources that are needed for production but also considers the productivity levels and the state of the production lines. In this context, online anomaly detection (AD) is an important tool for maintaining the reliability of the production ecosystem. With advancements in artificial intelligence and the growing significance of identifying and mitigating anomalies across different fields, approaches based on artificial neural networks facilitate the recognition of intricate types of anomalies by taking into account both temporal and contextual attributes. In this paper, a lightweight framework based on the Echo State Network (ESN) model running at the edge is introduced for online AD. Compared to other AD methods, such as Long Short-Term Memory (LSTM), it achieves superior precision, accuracy, and recall metrics while reducing training time, CO2 emissions, and the need for high computational resources. The preliminary evaluation of the proposed solution was conducted using a low-resource computing device at the edge of the real production machine through an Industrial Internet of Things (IIoT) smart meter module. The machine used to test the proposed solution was provided by the Italian company SIFIM Srl, which manufactures filter mats for industrial kitchens. Experimental results demonstrate the feasibility of developing an AD method that achieves high accuracy, with the ESN-based framework reaching 85 % compared to 80.88 % for the LSTM-based model. Furthermore, this method requires minimal hardware resources, with a training time of 9.5 s compared to 2.100 s for the other model. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Assistive Robot for Mobility Enhancement of Impaired Students for Barrier-Free Education: A Proof of Concept

Author

Freddi, Alessandro, Giaconi, Catia, Iarlori, Sabrina, Longhi, Sauro, Monteriù, Andrea, Pagnotta, Daniele Proietti, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Scaradozzi, David, editor, Guasti, Lorenzo, editor, Di Stasio, Margherita, editor, Miotti, Beatrice, editor, Monteriù, Andrea, editor, and Blikstein, Paulo, editor

Published
2021
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17. From the Control Systems Theory to Intelligent Manufacturing and Services: Challenges and Future Perspectives

Author

Bonci, Andrea, Conte, Giuseppe, Corradini, Maria Letizia, Freddi, Alessandro, Ietto, Leopoldo, Ippoliti, Gianluca, Longhi, Sauro, Monteriù, Andrea, Orlando, Giuseppe, Orsini, Valentina, Perdon, Anna Maria, Scaradozzi, David, Zanoli, Silvia Maria, Longhi, Sauro, editor, Monteriù, Andrea, editor, Freddi, Alessandro, editor, Frontoni, Emanuele, editor, Germani, Michele, editor, and Revel, Gian Marco, editor

Published
2019
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19. Smart Monitoring of User and Home Environment: The Health@Home Acquisition Framework

Author

Pietroni, Filippo, Casaccia, Sara, Revel, Gian Marco, Prist, Mariorosario, Monteriù, Andrea, Longhi, Sauro, Scalise, Lorenzo, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Casiddu, Niccolò, editor, Porfirione, Claudia, editor, Monteriù, Andrea, editor, and Cavallo, Filippo, editor

Published
2019
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21. Information Management and Decision Making Supported by an Intelligence System in Kitchen Fronts Control Process

Author

Stadnicka, Dorota, Bonci, Andrea, Pirani, Massimiliano, Longhi, Sauro, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Burduk, Anna, editor, and Mazurkiewicz, Dariusz, editor

Published
2018
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25. Conclusions

Author

Monteriù, Andrea, primary, Freddi, Alessandro, additional, and Longhi, Sauro, additional

Published
2020
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26. Self-similar Computing Structures for CPSs: A Case Study on POTS Service Process

Author

Stadnicka, Dorota, Pirani, Massimiliano, Bonci, Andrea, Chandima Ratnayake, R. M., Longhi, Sauro, Rannenberg, Kai, Editor-in-chief, Sakarovitch, Jacques, Series editor, Goedicke, Michael, Series editor, Tatnall, Arthur, Series editor, Neuhold, Erich J., Series editor, Pras, Aiko, Series editor, Tröltzsch, Fredi, Series editor, Pries-Heje, Jan, Series editor, Whitehouse, Diane, Series editor, Reis, Ricardo, Series editor, Furnell, Steven, Series editor, Furbach, Ulrich, Series editor, Winckler, Marco, Series editor, Rauterberg, Matthias, Series editor, Camarinha-Matos, Luis M., editor, Afsarmanesh, Hamideh, editor, and Fornasiero, Rosanna, editor

Published
2017
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31. A Database-Centric Framework for the Modeling, Simulation, and Control of Cyber-Physical Systems in the Factory of the Future

Author

Bonci Andrea, Pirani Massimiliano, and Longhi Sauro

Subjects
database management systems, distributed computer control systems, embedded systems, industry automation, intelligent manufacturing systems, simulators, 68, 93, 94, Science, Electronic computers. Computer science, QA75.5-76.95
Abstract

The factory of the future scenario asks for new approaches to cope with the incoming challenges and complexity of cyber-physical systems. The role of database management systems is becoming central for control and automation technology in this new industrial scenario. This article proposes database-centric technology and architecture that aims to seamlessly integrate networking, artificial intelligence, and real-time control issues into a unified model of computing. The proposed methodology is also viable for the development of a framework that features simulation and rapid prototyping tools for smart and advanced industrial automation. The full expression of the potentialities in the presented approach is expected in particular for applications where tiny and distributed embedded devices collaborate to a shared computing task of relevant complexity.

Published
2018
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46. Data Collection

Author

Gemelli, Alberto, Mancini, Adriano, Diamantini, Claudia, Longhi, Sauro, Gemelli, Alberto, Mancini, Adriano, Diamantini, Claudia, and Longhi, Sauro

Published
2013
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