1.
Partovian, Sania, et al.
(författare)
Analysis of log files to enable smart-troubleshooting in Industry 4.0 : a systematic mapping study
Ingår i: IEEE Access. - 2169-3536.
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt) abstract
A crucial element of Industry 4.0, is the utilization of smart devices that generate log files. Log files are key components containing data on system operations, faults (unexpected glitches or malfunctions), errors (mistakes or incorrect actions), and failures (complete breakdowns or non-functionality). This paper presents a systematic mapping study analyzing research conducted on log files for smart-troubleshooting in Industry 4.0. To the best of our knowledge, this is the study that aims to identify research trends, log file attributes, techniques, and challenges involved in log file analysis for smart-troubleshooting. From an initial set of 941 potentially relevant peer-reviewed publications, 74 primary studies were selected and analyzed using a meticulous data extraction, analysis, and synthesis process. The results of the study demonstrate that the majority of research has focused on developing algorithms for log analysis, with machine learning being the most commonly used approach. The smart-troubleshooting encompasses a range of activities and tools that are essential for collecting failure data generated by diverse interconnected devices, conducting analyses, and aligning them with troubleshooting instructions and software remedies. Moreover, the study identifies the need for further research in the areas of real-time log analysis, anomaly detection, and the integration of log analysis with other Industry 4.0 technologies. In conclusion, our study provides insights into the current state of research in log analysis for smart-troubleshooting in Industry 4.0 and identifies areas for future research. The use of smart devices generating log files in Industry 4.0 highlights the importance of log file analysis for troubleshooting purposes. Further research is needed to address the challenges and opportunities in this field to integrate log analysis with other Industry 4.0 technologies for performing more efficient and effective troubleshooting.
2.
Flammini, Francesco, Senior Lecturer, 1978-, et al.
(författare)
Multiformalism techniques for critical infrastructure modeling
2010
Ingår i: International Journal of System of Systems Engineering. - 1748-0671 .- 1748-068X. ; 2:1, s. 19-37
Tidskriftsartikel (refereegranskat) abstract
This paper proposes an approach to use multiformalism techniques for critical infrastructure modelling. To this aim, the state of the art of related works on the subject is surveyed and a general scheme for intra and inter infrastructure models is described. Multiformalism approaches allow modellers to adapt the choice of formal languages to the nature, complexity and abstraction layer of the subsystems to be modelled. Another advantage is the possibility of reusing existing dependability models and solvers. Complexity and heterogeneity are managed through modularity, and composition allows for representing structural or functional dependencies. An example model based on a railway infrastructure is used to illustrate the concepts introduced by the paper. Copyright © 2010 Inderscience Enterprises Ltd.
3.
Flammini, Francesco, Senior Lecturer, 1978-, et al.
(författare)
Safety integrity through self-adaptation for multi-sensor event detection : Methodology and case-study
2020
Ingår i: Future Generation Computer Systems. - : Elsevier. - 0167-739X .- 1872-7115. ; 112, s. 965-981
Tidskriftsartikel (refereegranskat) abstract
Traditional safety-critical systems are engineered in a way to be predictable in all operating conditions. They are common in industrial automation and transport applications where uncertainties (e.g., fault occurrence rates) can be modeled and precisely evaluated. Furthermore, they use high-cost hardware components to increase system reliability. On the contrary, future systems are increasingly required to be "smart"(or "intelligent") that is to adapt to new scenarios, learn and react to unknown situations, possibly using low-cost hardware components. In order to move a step forward to fulfilling those new expectations, in this paper we address run-time stochastic evaluation of quantitative safety targets, like hazard rate, in self-adaptive event detection systems by using Bayesian Networks and their extensions. Self-adaptation allows changing correlation schemes on diverse detectors based on their reputation, which is continuously updated to account for performance degradation as well as modifications in environmental conditions. To that aim, we introduce a specific methodology and show its application to a case-study of vehicle detection with multiple sensors for which a real-world data-set is available from a previous study. Besides providing a proof-of-concept of our approach, the results of this paper pave the way to the introduction of new paradigms in the dynamic safety assessment of smart systems. (c) 2020 Elsevier B.V. All rights reserved.
4.
Flammini, Francesco, Senior Lecturer, 1978-, et al.
(författare)
Wireless sensor data fusion for critical infrastructure security
2009
Ingår i: Proceedings of the International Workshop on Computational Intelligence in Security for Information Systems CISIS’08.. - Berlin, Heidelberg : Springer. - 9783540881803 ; , s. 92-99
Konferensbidrag (refereegranskat) abstract
Wireless Sensor Networks (WSN) are being investigated by the research community for resilient distributed monitoring. Multiple sensor data fusion has proven as a valid technique to improve detection effectiveness and reliability. In this paper we propose a theoretical framework for correlating events detected by WSN in the context of critical infrastructure protection. The aim is to develop a decision support and early warning system used to effectively face security threats by exploiting the advantages of WSN. The research addresses two relevant issues: the development of a middleware for the integration of heterogeneous WSN (SeNsIM, Sensor Networks Integration and Management) and the design of a model-based event correlation engine for the early detection of security threats (DETECT, DEcision Triggering Event Composer & Tracker). The paper proposes an overall system architecture for the integration of the SeNsIM and DETECT frameworks and provides example scenarios in which the system features can be exploited. © 2009 Springer-Verlag Berlin Heidelberg.
5.
Meo, Carlo Di, et al.
(författare)
ERTMS/ETCS Virtual Coupling : Proof of Concept and Numerical Analysis
2019
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 21:6, s. 2545-2556
Tidskriftsartikel (refereegranskat) abstract
Railway infrastructure operators need to push their network capacity up to their limits in high-traffic corridors. Virtual coupling is considered among the most relevant innovations to be studied within the European Horizon 2020 Shift2Rail Joint Undertaking as it can drastically reduce headways and thus increase the line capacity by allowing to dynamically connect two or more trains in a single convoy. This paper provides a proof of concept of Virtual coupling by introducing a specific operating mode within the European rail traffic management system/European train control system (ERTMS/ETCS) standard specification, and by defining a coupling control algorithm accounting for time-varying delays affecting the communication links. To that aim, we define one ploy to enrich the ERTMS/ETCS with Virtual coupling without changing its working principles and we borrow a numerical analysis methodology used to study platooning in the automotive field. The numerical analysis is also provided to support the proof of concept with quantitative results in a case-study simulation scenario.
6.
Assenza, Giacomo, et al.
(författare)
White Paper on Industry Experiences in Critical Information Infrastructure Security : A Special Session at CRITIS 2019
2020
Ingår i: Critical Information Infrastructures Security14th International Conference, CRITIS 2019. - Cham : Springer. - 9783030376697 - 9783030376703 ; , s. 197-207
Bokkapitel (refereegranskat) abstract
The security of critical infrastructures is of paramount importance nowadays due to the growing complexity of components and applications. This paper collects the contributions to the industry dissemination session within the 14th International Conference on Critical Information Infrastructures Security (CRITIS 2019). As such, it provides an overview of recent practical experience reports in the field of critical infrastructure protection (CIP), involving major industry players. The set of cases reported in this paper includes the usage of serious gaming for training infrastructure operators, integrated safety and security management in the chemical/process industry, risks related to the cyber-economy for energy suppliers, smart troubleshooting in the Internet of Things (IoT), as well as intrusion detection in power distribution Supervisory Control And Data Acquisition (SCADA). The session has been organized to stimulate an open scientific discussion about industry challenges, open issues and future opportunities in CIP research.
7.
Besinovic, Nikola, et al.
(författare)
Artificial Intelligence in Railway Transport : Taxonomy, Regulations, and Applications
2022
Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:9, s. 14011-14024
Tidskriftsartikel (refereegranskat) abstract
Artificial Intelligence (AI) is becoming pervasive in most engineering domains, and railway transport is no exception. However, due to the plethora of different new terms and meanings associated with them, there is a risk that railway practitioners, as several other categories, will get lost in those ambiguities and fuzzy boundaries, and hence fail to catch the real opportunities and potential of machine learning, artificial vision, and big data analytics, just to name a few of the most promising approaches connected to AI. The scope of this paper is to introduce the basic concepts and possible applications of AI to railway academics and practitioners. To that aim, this paper presents a structured taxonomy to guide researchers and practitioners to understand AI techniques, research fields, disciplines, and applications, both in general terms and in close connection with railway applications such as autonomous driving, maintenance, and traffic management. The important aspects of ethics and explainability of AI in railways are also introduced. The connection between AI concepts and railway subdomains has been supported by relevant research addressing existing and planned applications in order to provide some pointers to promising directions.
8.
9.
Bucaioni, Alessio, 1987-, et al.
(författare)
Towards Model-Based Performability Evaluation of Production Systems
2020
Ingår i: Work-in-progress at IEEE International Conference on Emerging Technologies and Factory Automation WIP@ETFA. - 9781728189567 ; , s. 1085-1088
Konferensbidrag (refereegranskat) abstract
Future smart factories will be increasingly required to predict expected performance and dependability metrics related to their production processes. Domain-specific metrics include overall equipment effectiveness that measures production system availability/uptime, performance/speed and output quality. In this work-in-progress paper, we take initial steps towards a model-based approach to evaluate production-specific metrics using domain-specific languages, model transformations and stochastic modelling formalism
10.
Buemi, Francesco, et al.
(författare)
Empty vehicle detection with video analytics
2013
Ingår i: Image Analysis and Processing – ICIAP 2013. ICIAP 2013. - Berlin, Heidelberg : Springer. - 9783642411830 - 9783642411847 ; , s. 731-739
Konferensbidrag (refereegranskat) abstract
An important issue to be addressed in transit security, in particular for driverless metro, is the assurance that a vehicle is empty before it returns to the depot. Customer specifications in recent tenders require that an automatic empty vehicle detector is provided. That improves system security since it prevents voluntary (e.g. in case of thieves or graffiti makers) or involuntary (e.g. in case of drunk or unconscious people) access of unauthorized people to the depot and possibly to other restricted areas. Without automatic systems, a manual inspection of the vehicle should be performed, requiring considerable personnel effort and being prone to failure. To address the issue, we have developed a reliable empty vehicle detection system using video content analytics techniques and standard on-board cameras. The system can automatically check whether the vehicles have been cleared from passengers, thus supporting the security staff and central control operators in providing a higher level of security. © 2013 Springer-Verlag.
