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Research Papers

Dynamic Computation of Time-Varying Spatial Contexts

[+] Author and Article Information
Imre Horváth

Fellow ASME
Industrial Design Engineering,
Delft University of Technology,
Landbergstraat 15,
Delft 2628CE, The Netherlands
e-mail: i.horvath@tudelft.nl

Yongzhe Li

Industrial Design Engineering,
Delft University of Technology,
Landbergstraat 15,
Delft 2628CE, The Netherlands
e-mail: y.li-8@tudelft.nl

Zoltán Rusák

Industrial Design Engineering,
Delft University of Technology,
Landbergstraat 15,
Delft 2628CE, The Netherlands
e-mail: z.rusak@tudelft.nl

Wilhelm Frederik van der Vegte

Industrial Design Engineering,
Delft University of Technology,
Landbergstraat 15,
Delft 2628CE, The Netherlands
e-mail: w.f.vandervegte@tudelft.nl

Guangjun Zhang

State Key Laboratory of
Advanced Welding and Joining,
Harbin Institute of Technology,
92 West Dazhi Street,
Harbin 150001, China
e-mail: zhanggj@hit.edu.cn

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received February 12, 2016; final manuscript received June 22, 2016; published online November 7, 2016. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 17(1), 011007 (Nov 07, 2016) (12 pages) Paper No: JCISE-16-1077; doi: 10.1115/1.4034034 History: Received February 12, 2016; Revised June 22, 2016

There are many real-life processes whose smart control requires processing context information. Though processing time-varied context information is addressed in the literature, domain-independent solutions for reasoning about time-varying process scenarios are scarce. This paper proposes a method for dynamic context computation concerning spatial and attributive information. Context is interpreted as a body of information dynamically created by a pattern of entities and relationships over a history of situations. Time is conceived as a causative force capable of changing situations and acting on people and objects. The invariant and variant spatial information is captured by a two-dimensional spatial feature representation matrix (SFR-matrix). The time-dependent changes in the context information are computed based on a dynamic context information (DCI) management hyper-matrix. This humble but powerful representation lends itself to a quasi-real time computing and is able to provide information about foreseeable happenings over multiple situations. Based on this, the reasoning mechanism proposed in this paper is able to provide informative instructions for users who needed to be informed in a dynamically changing situation. This paper uses the practical case of evacuation of a building in fire both as an explorative case for conceptualization of the functionality of the computational mechanism and as a demonstrative and testing application. Our intention is to use the dynamic context computation mechanism as a kernel component of a reasoning platform for informing cyber-physical systems (I-CPSs). Our future research will address the issue of context information management for multiple interrelated spaces.

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References

Buchholz, T. , Küpper, A. , and Schiffers, M. , 2003, “ Quality of Context Information: What It is and Why We Need It,” 10th International Workshop of the HP OpenView University Association (HPOVUA'01), Vol. 2003.
Da Rocha, R. C. , and Endler, M. , 2012, Context Management for Distributed and Dynamic Context-Aware Computing, Springer Science & Business Media, London, UK, pp. 1–92.
Tanca, L. , Bolchini, C. , Quintarelli, E. , Schreiber, F. A. , and Orsi, G. , 2011, “ Problems and Opportunities in Context-Based Personalization,” VLDB Endowment, 4(11), pp. 1–4. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.648.6576'rep=rep1'type=pdf
Lee, I. , Sokolsky, O. , Chen, S. , Hatcliff, J. , Jee, E. , Kim, B. , and Venkatasubramanian, K. K. , 2012, “ Challenges and Research Directions in Medical Cyber-Physical Systems,” Proc. IEEE, 100(1), pp. 75–90. [CrossRef]
Gwizdka, J. , 2000, “ What's in the Context,” Computer Human Interaction, Vol. 2000, pp. 1–4.
Abowd, G. D. , Dey, A. K. , Brown, P. J. , Davies, N. , Smith, M. , and Steggles, P. , 1999, “ Towards a Better Understanding of Context and Context-Awareness,” Handheld and Ubiquitous Computing, Springer, Berlin, pp. 304–307.
Debes, M. , Lewandowska, A. , and Seitz, J. , 2005, “ Definition and Implementation of Context Information,” Second Joint Workshop on Positioning, Navigation and Communication, pp. 63–68. https://www.researchgate.net/profile/Jochen_Seitz3/publication/228938094_Definition_and_Implementation_of_Context_Information/links/0046352a032466a41a011007.pdf
Dey, A. K. , and Abowd, G. D. , 1997, “ CyberDesk: The Use of Perception in Context-Aware Computing (Extended Abstract),” Workshop on Perceptual User Interfaces, Oct. 19–21, pp. 26–27.
Dey, A. K. , and Abowd, G. D. , 2000, “ Towards a Better Understanding of Context and Context-Awareness,” Workshop on What, Who, Where, When, and How of Context-Awareness, CHI.
Schmidt, A. , Beigl, M. , and Gellersen, H. W. , 1999, “ There is More to Context Than Location,” Comput. Graphics, 23(6), pp. 893–901. [CrossRef]
Strang, T. , and Linnhoff-Popien, C. , 2004, “ A Context Modeling Survey,” First International Workshop on Advanced Context Modelling, Reasoning and Management, Nottingham, UK. http://elib.dlr.de/7444/
Fernández-de-Alba, J. M. , Fuentes-Fernández, R. , and Pavón, J. , 2015, “ Architecture for Management and Fusion of Context Information,” Inf. Fusion, 21(1), pp. 100–113. [CrossRef]
Malandrino, D. , Mazzoni, F. , Riboni, D. , Bettini, C. , Colajanni, M. , and Scarano, V. , 2010, “ MIMOSA: Context-Aware Adaptation for Ubiquitous Web Access,” Pers. Ubiquitous Comput., 14(4), pp. 301–320. [CrossRef]
Fuchs, F. , Hochstatter, I. , Krause, M. , and Berger, M. , 2005, “ A Metamodel Approach to Context Information,” Third International Conference on Pervasive Computing and Communications Workshops, Los Alamitas, CA, IEEE, pp. 8–14. http://www.mnm-team.org/common/pub/Publikationen/fhkb05/PDF-Version/fhkb05.pdf
Henricksen, K. , Indulska, J. , and Rakotonirainy, A. , 2002, “ Modeling Context Information in Pervasive Computing Systems,” Pervasive Computing, Springer, Berlin, pp. 167–180.
Castro, P. , and Munz, R. , 2000, “ Managing Context Data for Smart Spaces,” IEEE Pers. Commun., 7(5), pp. 44–46. [CrossRef]
Henricksen, K. , and Indulska, J. , 2004, “ Modelling and Using Imperfect Context Information,” Second Annual Conference on Pervasive Computing and Communications Workshops, Orlando, FL, Mar. 14–17, IEEE, pp. 33–37.
van Kranenburg, H. , and Eertink, H. , 2005, “ Processing Heterogeneous Context Information,” International Symposium on Applications and the Internet Workshops, pp. 140–143.
Gu, T. , Wang, X. H. , Pung, H. K. , and Zhang, D. Q. , 2004, “ An Ontology-Based Context Model in Intelligent Environments,” Communication Networks and Distributed Systems Modeling and Simulation Conference, pp. 270–275. http://www-public.tem-tsp.eu/~zhang_da/pub/Ontology-2004-2.pdf
Wang, X. H. , Zhang, D. Q. , Gu, T. , and Pung, H. K. , 2004, “ Ontology Based Context Modeling and Reasoning Using OWL,” Second Annual Conference on Pervasive Computing and Communications Workshops, Orlando, FL, Mar. 14–17, IEEE, pp. 18–22.
Kokinov, B. , 1995, “ A Dynamic Approach to Context Modeling,” LAFORIA, 95(11), pp. 199–209.
Forsström, S. , and Kanter, T. , 2012, “ Enabling Continuously Evolving Context Information in Mobile Environments by Utilizing Ubiquitous Sensors,” Mobile Networks and Management, Springer, Berlin, pp. 289–303.
Euzenat, J. , Pierson, J. , and Ramparany, F. , 2008, “ Dynamic Context Management for Pervasive Applications,” Knowl. Eng. Rev., 23(1), pp. 21–49. [CrossRef]
Kim, Y. , and Mahapatra, R. N. , 2009, “ Dynamic Context Management for Low Power Coarse-Grained Reconfigurable Architecture,” 19th ACM Great Lakes Symposium on VLSI, Boston, MA, ACM, New York, pp. 33–38.
Brown, P. J. , 1996, “ The Stick-e Document: A Framework for Creating Context-Aware Applications,” Electron. Publishing, 8(2–3), pp. 259–272. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.8.7472'rep=rep1'type=pdf
Aktas, M. S. , Fox, G. C. , and Pierce, M. , 2005, “ Managing Dynamic Metadata as Context,” International Computational Science and Engineering Conference, Istanbul, Turkey. https://www.researchgate.net/profile/Geoffrey_Fox/publication/242371440_Managing_Dynamic_Metadata_as_Context/links/0046352948ece189fe011007.pdf
Grossmann, M. , Bauer, M. , Hönle, N. , Käppeler, U. P. , Nicklas, D. , and Schwarz, T. , 2005, “ Efficiently Managing Context Information for Large-Scale Scenarios,” Third International Conference on Pervasive Computing and Communications, Kauai, HI, Mar. 8–12, IEEE, pp. 331–340.
Taconet, C. , Kazi-Aoul, Z. , Zaier, M. , and Conan, D. , 2009, “ Ca3M: A Runtime Model and a Middleware for Dynamic Context Management,” On the Move to Meaningful Internet Systems: OTM 2009, Springer, Berlin, pp. 513–530.
Villegas, N. M. , Müller, H. A. , Muñoz, J. C. , Lau, A. , Ng, J. , and Brealey, C. , 2011, “ A Dynamic Context Management Infrastructure for Supporting User-Driven Web Integration in the Personal Web,” 2011 Conference of the Center for Advanced Studies on Collaborative Research, Toronto, ON, Canada, IBM, Riverton, NJ, pp. 200–214. http://dl.acm.org/citation.cfm?id=2093913
Jaroucheh, Z. , Liu, X. , and Smith, S. , 2010, “ CANDEL: Product Line Based Dynamic Context Management for Pervasive Applications,” 2010 International Conference on Complex, Intelligent and Software Intensive Systems, Krakow, Poland, Feb. 15–18, IEEE, pp. 209–216.
Dey, A. K. , Abowd, G. D. , and Salber, D. , 2001, “ A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications,” Hum. Comput. Interact., 16(2), pp. 97–166. [CrossRef]
Kwon, O. , 2006, “ The Potential Roles of Context-Aware Computing Technology in Optimization-Based Intelligent Decision-Making,” Expert Syst. Appl., 31(3), pp. 629–642. [CrossRef]
Brown, P. J. , Bovey, J. D. , and Chen, X. , 1997, “ Context-Aware Applications: From the Laboratory to the Marketplace,” IEEE Pers. Commun., 4(5), pp. 58–64. [CrossRef]
Anthony, R. , Chen, D. , Pelc, M. , Persson, M. , and Törngren, M. , 2009, “ Context-Aware Adaptation in DYSCAS,” Electron. Commun. EASST, 19, pp. 1–15. http://gala.gre.ac.uk/5533/
Dai, P. , and Xu, G. , 2008, “ Context-Aware Computing for Assistive Meeting System,” 1st International Conference on Pervasive Technologies Related to Assistive Environments, Athens, Greece, ACM.
Baldauf, M. , Dustdar, S. , and Rosenberg, F. , 2007, “ A Survey on Context-Aware Systems,” Int. J. Ad Hoc Ubiquitous Comput., 2(4), pp. 263–277. [CrossRef]
Vieira, V. , Tedesco, P. , and Salgado, A. C. , 2011, “ Designing Context-Sensitive Systems: An Integrated Approach,” Expert Syst. Appl., 38(2), pp. 1119–1138. [CrossRef]
Cortez, R. A. , 2009, “ A Cyber-Physical System for Situation Awareness Following a Disaster Situation,” Realtime Systems Symposium, Washington, DC, IEEE. https://www.researchgate.net/profile/R_Cortez/publication/268178821_A_Cyber-Physical_System_for_Situation_Awareness_Following_a_Diaster_Situation/links/554cb0b30cf21ed2135bf4da.pdf

Figures

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Fig. 1

Basic constituents of an informing CPS

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Fig. 4

Hyper-matrix for DCI management

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Fig. 5

Reasoning mechanism used for developing personalized evacuation strategies

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Fig. 6

Typical attribute profiles used in the SFRH-matrix: (a) attribute profile of an exit and (b) attribute profile of a person

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Fig. 7

Time periods available for using different types of exits

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Fig. 8

Flowchart of the algorithm used to develop raw strategy

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Fig. 9

Flowchart of the algorithm used to refine the escape strategy considering human dynamics

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Fig. 10

Time needed by the different category of people to escape in different situations

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Fig. 11

Flowchart of the algorithm used to reduce the number of people involved in a jam

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Fig. 12

Floor plan of the considered building: (a) physical arrangement of the space and (b) the starting place of fire

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Fig. 13

Simulation of the indoor fire situations without informing by the system at (a) T = 20 s, (b) T = 80 s, and (c) T = 200 s

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Fig. 14

Simulation of the indoor fire situations with informing by the system at (a) T = 30 s, (b) T = 50 s, (c) T = 80 s, and (d) T = 200 s

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Fig. 15

The number of people trapped in a jam at various exits: (a) without reducing the number of people potentially involved in jam and (b) with application of strategy refinement in step 2

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