A generalized model for quantifying the impact of Ambient Intelligence on smart workplaces: Applications in manufacturing

Journal of Ambient Intelligence and Smart Environments

Volumn 6, Issue 6, 2014, Pages 651-673

  Aly, Shady ^a,b,c   Pelikán, Martin ^a   Vrana, Ivan ^a  

^a Engineering Department   (Egypt)

^b CZECH UNIVERSITY OF LIFE SCIENCES PRAGUE   (Czech Republic)

^c KING SAUD UNIVERSITY   (Saudi Arabia)

Author keywords

Ambient Intelligence (AmI); Fuzzy Analytical Hierarchical Process (Fuzzy AHP); manufactur ing systems; Multi criteria Decision Analysis (MCDA); Smart environment workplaces

Indexed keywords

ARTIFICIAL INTELLIGENCE; FUZZY RULES; HIERARCHICAL SYSTEMS;

AMBIENT INTELLIGENCE; ENABLING TECHNOLOGIES; FUZZY AHP; IMPROVING PERFORMANCE; LOGICAL RELATIONSHIPS; MULTI-CRITERIA DECISION ANALYSIS; PERFORMANCE MEASURE; SMART ENVIRONMENT;

MANUFACTURE;

EID: 84914673973     PISSN: 18761364     EISSN: None     Source Type: Journal    
DOI: 10.3233/AIS-140291     Document Type: Article

References (31)

1. ISTAG, IST Advisory Group, Advisory Group to the European Community's Information Society Technology Program, 2005, http://www.cordis.lu/ist/istag.htmi.
2. D.J. Cook, J.C. Augusto and V.R. Jakkula, Ambient intelligence: Technologies, applications, and opportunities, Pervasive and Mobile Computing 5 (2009), 277-298.
3. J. Augusto, Ambient intelligence: The confluence of pervasive computing and artificial intelligence, in: Intelligent Computing Everywhere, A. Schuster, ed., Springer, 2007, pp. 213-234.
4. G. Riva, F. Vatalaro, F. Davide and M. Alcaniz, Ambient Intelligence. The Evolution of Technology, Comm. and Cognition Towards the Future of Human-Computer Interaction, IOS Press, Amsterdam, 2005, pp. 1-320.
5. E. Serrano and J. Botia, Validating ambient intelligence based ubiquitous computing systems by means of artificial societies, Information Sciences 222 (2013), 3-24.
6. X. Hu, W. Du and B. Spencer, A multi-agent framework for Ambient systems development, Procedia Computer Science 5 (2011), 82-89.
7. D.I. Tapia, J.A. Fraile, S. Rodríguez, R.S. Alonso and J.M. Corchado, Integrating hardware agents into an enhanced multi-agent architecture for Ambient Intelligence systems, Information Sciences 222 (2013), 47-65.
8. M.J. Santofimia, S.E. Fahlman, X. del Toro, F. Moya and J.C. Lopez, A semantic model for actions and events in Ambient Intelligence, Engineering Applications of Artificial Intelligence 24(8) (2011), 1432-1445.
9. T. Bosse, F. Both, C. Gerritsen, M. Hoogendoorn and Jan Treur, Methods for model-based reasoning within agentbased Ambient Intelligence applications, Knowledge-Based Systems 27 (2012), 190-210.
10. N. Dipsis and K. Stathis, Ubiquitous agents for Ambient ecologies, Pervasive and Mobile Computing 8(4) (2012), 562-574.
11. K. Vila, J.-N. Mázon and A. Feŕrandez, Model-driven adaptation of question answering systems for Ambient Intelligence by integrating restricted-domain knowledge, Procedia Computer Science 4 (2011), 1650-1659.
12. A. De Paola, S. Gaglio, G. Lo Re and M. Ortolani, Sensor9k: A testbed for designing and experimenting with WSN-based Ambient Intelligence applications, Pervasive and Mobile Computing 8(3) (2012), 448-466.
13. G. Kovács, S. Kopácsi, G. Haidegger and R. Michelini, Ambient Intelligence in product life-cycle management, Engineering Applications of Artificial Intelligence 19 (2006), 953-965.
14. S. Kopácsi, G. Kovács, A. Anufriev and R. Michelini, Ambient intelligence as enabling technology for modern business paradigms, Robotics and Computer-Integrated Manufacturing 23(2) (2007), 242-256.
15. I. Maurtua, M.A. Pérez, L. Susperregi, C. Tubio and A. Ibarguren, in: Ambient Intelligence in Manufacturing, Intelligent Production Machines and Systems, 2nd IPROMS International Virtual Conference, July 2006, pp. 535-540.
16. F. Doctor, H. Hagras and V. Callaghan, A type-2 fuzzy embedded agent to realize Ambient Intelligence in ubiquitous computing environments, Information Sciences 171(4) (2005), 309-334.
17. G. Acampora and V. Loia, A proposal of ubiquitous fuzzy computing for Ambient Intelligence, Information Sciences 178(3) (2008), 631-646.
18. I. Vrana and S. Aly, Conceptual models for managerial Ambient Intelligence, in: Ambient Intelligence forum, Hradec Kralove, Sept, 2009, Czech Republic, Ambient Intelligence Perspectives II, IOS Press, 2009, pp. 53-63.
19. S. Aly and I. Vrana, Objective measurement of Ambient Intelligence influence on decision support in smart offices, in: Proc. of the 11th Smart Offices and Other Workplaces (SOOW'11) Workshop, The 7th International Conference on Intelligent Environments, 25-28 July, Nottingham, United Kingdom, 2011.
20. J.-Y. Hong, E.-H. Suh and S.-J. Kim, Context-aware systems: A literature review and classification, Expert Systems with Applications 36(4) (2008), 8509-8522.
21. J.C. Augusto, Ambient Intelligence: Basic concepts and applications, in: ICSOFT 2006, J. Filipe, B. Shishkov and M. Helfert, eds, CCIS, Vol. 10, Springer-Verlag, Berlin, Heidelberg, 2008, pp. 16-26.
22. T.L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, NY, 1980.
23. S. Aly and I. Vrana, Evaluating the knowledge, relevance and experience of expert decision makers utilizing the Fuzzy-AHP, Agriculture Economics-Czech Republic 54(11) (2008), 529-535.
24. P.J.M. Laarhoven andW. Pedrycz, A fuzzy extension of Saaty's priority theory, Fuzzy Sets and Systems 11 (1983), 229-241.
25. M. Dagdeviren and I. Yuksel, Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management, Information Sciences 178(6) (2008), 1717-1733.
26. M.F. Chen, G.H. Tzeng and C.G. Ding, Combining fuzzy AHP with MDS in identifying the preference similarity of alternatives, Applied Soft Computing 8(1) (2008), 110-117.
27. K.K.B. Hon, Performance and evaluation of manufacturing systems (keynote paper), Annals of CIRP 52(2) (2005), 675-690.
28. S. Aly, Integrating multiple fuzzy expert systems under varying requirements, PhD thesis, Czech University of Life Science in Prague, Prague, Czech Republic, 2006.
29. Y.-C. Choua, C.-C. Sunb and H.-Y. Yenc, Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach, Applied Soft Computing 12 (2012), 64-71.
30. L.A. Zadeh, Fuzzy sets, Information and Control 8 (1965), 338-353.
31. M. Fasanghari, Knowledge management (intellectual capital) assessment using fuzzy expert system, in: Knowledge Management, P. Virtanen and N. Helander, eds, In-The, Croatia, 2010, pp. 15-24.