Advances in Aeronautical Informatics

This chapter draws the readers into a comprehensive discussion about the advances in Information and Communication Technologies (ICT) and their influence on the technology landscape of aeronautics. It gives a rough overview of the advances in technical systems from the industrial revolution up until Industry 4.0 and elaborates the reflection of these advancements in aeronautics from the pioneers era toward Flight 4.0. It briefly describes various recent fields of research in ICT such as Cyber-Physical Systems (CPS), Internet of Things (IoT), wireless networks, multicore architectures, Service-Oriented Architecture (SOA), cloud computing, big data, and modern software engineering methodologies as the parts of future aeronautical engineering body of knowledge. Thereafter, it describes aeronautical informatics as an establishing interdisciplinary field of study of applied informatics and aeronautics. 1.1 Aeronautics: The Study of Flight Aeronautics is defined as the study or the practice of all aspects of flight through the air [1]. It also refers to design, construction, and operation of aircraft [2]. Aeronautical engineering is the corresponding engineering discipline. It applies the scientific principles of flight and engineering in design and development of aircraft and its operation. Aerospace engineering extends the limits of aeronautical engineeringwith including space flight and astronautics into its scope. Encyclopedia of Aerospace Engineering from Wiley documents the aspiration of the largest professional organizations of aeronautics, namely Royal Aeronautical Society (RAeS) and the American Institute of Aeronautics and Astronautics (AIAA) in seeking the bodyof aerospace knowledge [3]. This large-scale reference that covers entire range of scientific and engineering principles of aeronautics and astronautics is organized in eight volumes: fluid dynamics and aerothermodynamics, propulsion and power, structural technology, materials technology, dynamics and control, U. Durak (B) German Aerospace Center (DLR), Braunschweig, Germany e-mail: umut.durak@dlr.de © Springer International Publishing AG, part of Springer Nature 2018 U. Durak et al. (eds.), Advances in Aeronautical Informatics, https://doi.org/10.1007/978-3-319-75058-3_1 3

[1]  Justyna Zander-Nowicka,et al.  Model-based Testing of Real-Time Embedded Systems in the Automotive Domain , 2009 .

[2]  O. Sander,et al.  The promised future of multi-core processors in avionics systems , 2017 .

[3]  L.M. Boden,et al.  Adding natural relationships to Simulink models to improve automated model-based testing , 2004, The 23rd Digital Avionics Systems Conference (IEEE Cat. No.04CH37576).

[4]  Okyay Kaynak,et al.  Big Data for Modern Industry: Challenges and Trends [Point of View] , 2015, Proc. IEEE.

[5]  Joshua Zhexue Huang,et al.  Big data analytics on Apache Spark , 2016, International Journal of Data Science and Analytics.

[6]  Alessandro Galli,et al.  Dynamic Data-driven Avionics Systems: Inferring Failure Modes from Data Streams , 2015, ICCS.

[7]  Christian Esposito,et al.  A knowledge-based platform for Big Data analytics based on publish/subscribe services and stream processing , 2015, Knowl. Based Syst..

[8]  Akshit Dhar Big Data Technologies for Batch and Real-Time Data Processing: A Review , 2017 .

[9]  Mario Piattini,et al.  Knowledge Discovery Metamodel-ISO/IEC 19506: A standard to modernize legacy systems , 2011, Comput. Stand. Interfaces.

[10]  S. Appavu alias Balamurugan,et al.  Prediction of warning level in aircraft accidents using data mining techniques , 2014, The Aeronautical Journal (1968).

[11]  Heiko Stallbaum,et al.  Toward DO-178B-compliant Test Models , 2010, 2010 Workshop on Model-Driven Engineering, Verification, and Validation.

[12]  Ettore Merlo,et al.  Adapting Software Product Lines for complex certifiable avionics software , 2012, 2012 Third International Workshop on Product LinE Approaches in Software Engineering (PLEASE).

[13]  Yi Yang,et al.  Civil Aircraft Big Data Platform , 2017, 2017 IEEE 11th International Conference on Semantic Computing (ICSC).

[14]  Jaejoon Lee,et al.  Incorporating certification in feature modelling of an unmanned aerial vehicle product line , 2012, SPLC '12.

[15]  Syed Akhter Hossain,et al.  NoSQL Database: New Era of Databases for Big data Analytics - Classification, Characteristics and Comparison , 2013, ArXiv.

[16]  Frank Dordowsky,et al.  Adopting software product line principles to manage software variants in a complex avionics system , 2009, SPLC.

[17]  Divesh Srivastava,et al.  Big data integration , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).

[18]  Yang Tao,et al.  Research on big data management and analysis method of multi-platform avionics system , 2017, 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS).

[19]  Giuseppe Visaggio,et al.  Journal of Software Maintenance and Evolution: Research and Practice Ageing of a Data-intensive Legacy System: Symptoms and Remedies , 2022 .

[20]  Ka-Chun Wong,et al.  A Short Survey on Data Clustering Algorithms , 2015, 2015 Second International Conference on Soft Computing and Machine Intelligence (ISCMI).

[21]  Sven Hartmann,et al.  A Fast Heuristic for Finding Near-Optimal Groups for Vehicle Platooning in Road Networks , 2017, DEXA.

[22]  Carlos A. Varela,et al.  Autonomous Data Error Detection and Recovery in Streaming Applications , 2013, ICCS.

[23]  M.M. Lehman,et al.  Programs, life cycles, and laws of software evolution , 1980, Proceedings of the IEEE.

[24]  Isabela Xavier Castilho Fault prediction in aircraft tires using Bayesian Networks , 2015 .

[25]  Asok Ray,et al.  Data-Driven Fault Detection in Aircraft Engines With Noisy Sensor Measurements , 2011 .

[26]  Rick Kazman,et al.  How Lufthansa Capitalized on Big Data for Business Model Renovation , 2017, MIS Q. Executive.

[28]  Athanasios V. Vasilakos,et al.  Data Mining for the Internet of Things: Literature Review and Challenges , 2015, Int. J. Distributed Sens. Networks.

[29]  G. Fitzgerald,et al.  'I. , 2019, Australian journal of primary health.

[30]  E. C. Larson,et al.  Model-based sensor and actuator fault detection and isolation , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[31]  Barbara Gallina,et al.  Deriving verification-related means of compliance for a model-based testing process , 2016, 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC).

[32]  Divesh Srivastava,et al.  Incremental Record Linkage , 2014, Proc. VLDB Endow..

[33]  Martin Simons,et al.  Model Aircraft Aerodynamics , 1983 .

[34]  Andreas Hein,et al.  Product Line Variability in Automotive Systems , 2002 .

[35]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[36]  Harry M. Sneed,et al.  Estimating the costs of a reengineering project , 2005, 12th Working Conference on Reverse Engineering (WCRE'05).

[37]  Viktor K. Decyk,et al.  RE-ENGINEERING LEGACY MISSION SCIENTIFIC SOFTWARE* , 2001 .

[38]  R.D. Busser,et al.  Reducing cost of high integrity systems through model-based testing , 2004, The 23rd Digital Avionics Systems Conference (IEEE Cat. No.04CH37576).

[39]  Thomas H. Davenport,et al.  Big Data at Work: Dispelling the Myths, Uncovering the Opportunities , 2014 .

[40]  Victor A. Skormin,et al.  Data mining technology for failure prognostic of avionics , 2002 .