Developing FIA5 to FSTPR25 for modeling spatio-temporal relevancy in context-aware wayfinding systems

  • Najmeh Neysani SamanyEmail author
  • Mahmoud Reza Delavar
  • Nicholas Chrisman
Original Research


Wayfinding or leading a moving user from an origin to a target is one of the main research focuses in urban context-aware systems. Space and time are two dominant properties of the context-aware wayfinding process and spatio-temporal relevancy between the fixed urban entities and the moving users determine whether an entity is related to the moving user or not. This paper specifically concentrates on the development of customized fuzzy interval algebra (FIA5) for detecting spatio-temporally relevant contexts to the user. This paper integrates fuzzy spatial and temporal intervals and customizes the spatio-temporal relations between the new data models—called fuzzy spatio temporal prism relevancy (FSTPR25) model-based on Allen’s fuzzy multi interval algebra. In this implementation, the FSTPR25 helps the tourist to find his/her preferred areas that are spatio-temporally relevant with two optimistic and pessimistic strategies. The experimental results in a scenario of tourist navigation are evaluated with respect to the accuracy of the model in 450 iterations of the algorithm in 15 different routes based on the statistical quantifiers in Tehran, Iran. The evaluation process demonstrated the high accuracy and user satisfaction of the optimistic strategy in real-world applications.


Context-awareness Spatio-temporal relevancy Customization Spatio-temporal prism Fuzzy interval algebra Tourist 



  1. Alegre U, Carlos Augusto J, Clark T (2016) Engineering context-aware systems and applications: a survey. J Syst Softw 117:55–83CrossRefGoogle Scholar
  2. Allen JF (1983) Maintaining knowledge about temporal intervals. J. Commun ACM 26(11):832–843CrossRefzbMATHGoogle Scholar
  3. Becker C, Nicklas D (2004) Where do spatial context-models end and where do ontologies start? A proposal of a combined approach. In: Proceedings of first international workshop on advanced context modelling, reasoning and management in conjunction with UbiComp2004, pp 48–53Google Scholar
  4. Bobek S, Nalepa GJ (2017) Uncertainty handling in rule-based mobile context-aware systems. Pervas Mob Comput 39:159–179CrossRefGoogle Scholar
  5. Bryant DJ, Tversky B, Lanca M (2000) Retrieving spatial relations from observation and memory. In: van der Zee E, Nikanne U (eds) Cognitive interfaces: constraints on linking cognitive information. Oxford University Press, Oxford, pp 94–115Google Scholar
  6. Cadenas JT, Marín N, Vila MA (2014) Context-aware fuzzy databases. J Appl Soft Comput 25:215–233CrossRefGoogle Scholar
  7. Choi D, Kim N, Tuan Hung D (2012) Conceptual data modeling for realizing context-aware services. J Expert Syst Appl 39:3022–3030CrossRefGoogle Scholar
  8. Cohn AG, Bennett B, Gooday J, Gotts NM (1997) Representing and reasoning with qualitative spatial relations about regions. Spatial and temporal reasoning. Kluwer Academic Publishers, Dordrecht, pp 97–134CrossRefGoogle Scholar
  9. Ducret R, Lemarié B, Roset A (2016) Cluster analysis and spatial modeling for urban freight. Identifying homogeneous urban zones based on urban form and logistics characteristics. J Trans Res Proc 12:301–313Google Scholar
  10. Gebbert S, Pebesma E (2014) A temporal GIS for field based environmental modeling. J Environ Model Softw 53:1–12CrossRefGoogle Scholar
  11. Golumbic MC, Shamir R (1993) Complexity and algorithms for reasoning about time: a graph theoretic approach. J ACM 40(5):1128–1133MathSciNetCrossRefzbMATHGoogle Scholar
  12. González JA, Rodríguez-Cortés FJ, Cronie O, Mateua J (2016) Spatio-temporal point process statistics: a review. J Spat Stat 18:505–544MathSciNetCrossRefGoogle Scholar
  13. Holzmann C, Ferscha A (2010) A framework for utilizing qualitative spatial relations between networked embedded systems. J Pervas Mob Comput 6:362–381CrossRefGoogle Scholar
  14. Hong J, Suh E-H, Kiim J, Kim S (2009) Context-aware system for proactive personalized service based on context history. J Expert Syst Appl 36:7448–7457CrossRefGoogle Scholar
  15. Jimenez-Molina A, Ko IY (2011) Spontaneous task composition in urban computing environments based on social, spatial and temporal aspects. J Eng Appl Artif Intell 24:1446–1460CrossRefGoogle Scholar
  16. Lauwereins S, Badami K, Meert W, Verhelst M (2015) Optimal resource usage in ultra-low-power sensor interfaces through context and resource-cost-aware machine learning. J Neurocomput 169:236–245CrossRefGoogle Scholar
  17. Lee J, Chang HL, Kim DW, Kang BY (2017) Smartphone-assisted pronunciation learning technique for ambient intelligence. IEEE Access 5(99):312–325CrossRefGoogle Scholar
  18. Lim BY, Dey AK (2009) Assessing demand for intelligibility in context-aware applications. UbiComp2009, Sep 30–Oct 3, Orlando, Florida, USA, pp 195–254Google Scholar
  19. Liu Ch, Park E-M, Jiang F (2018) Examining effects of context-awareness on ambient intelligence of logistics service quality: user awareness compatibility as a moderator. J Amb Intell Human Comput 9(48):1–8Google Scholar
  20. Mamdani EH (1977) Applications of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26(12):1182–1191CrossRefzbMATHGoogle Scholar
  21. Matsakis P, Wendling L, Ni JB (2010) A general approach to the fuzzy modeling of spatial relationships. Methods for handling imperfect spatial info, STUDFUZZI, p 256Google Scholar
  22. Neisany Samany N, Delavar MR, Saeedi S, Aghataher R (2009) 3D continuous K–NN query for a landmark-based wayfinding location-based service. 3D Geo-Inf Sci Lect Notes Geoinf Cartogr Part II:271–282Google Scholar
  23. Neysani Samany N, Delavar MR, Chrisman N, Malek MR (2013) Modeling spatio-temporal relevancy in context-aware systems using voronoi continuous range query and multi-interval algebra. J Mob Inf Syst 9:189–208Google Scholar
  24. Neysani Samany N, Delavar MR, Chrisman N, Malek MR (2014) FIA5: a customized fuzzy interval algebra for modeling spatial relevancy in urban context-aware systems. J Eng Appl Artif Intell 33:116–126CrossRefGoogle Scholar
  25. Olsson T, Kakkainen T, Lagerstam E, Venta- Olkonen L (2012) User evaluation of mobile augmented reality scenarios. J Amb Intel Smart Environ 4:29–47Google Scholar
  26. Pazhoumand-Dar H (2018) Fuzzy association rule mining for recognising daily activities using Kinect sensors and a single power meter. J Amb Intell Hum Comput 9(5):1497–1515CrossRefGoogle Scholar
  27. Reichenbacher T (2005) The concept of relevance in mobile maps. Location based services and tele-cartography. Lect Notes Geo-Inf Cartogr Section III:231–246Google Scholar
  28. Renz J, Schmid F (2007) Customizing qualitative spatial and temporal calculi. In: Orgun MA, Thornton J (eds) AI, vol LNAI 4830. Springer, Berlin, pp 293–304Google Scholar
  29. Salton G, McGill M (1984) Introduction to modern information retrieval. McGraw-Hill, New YorkzbMATHGoogle Scholar
  30. Schockaert S, Cock MD (2008) Temporal reasoning about fuzzy intervals. J Artif Intell 172:1158–1193MathSciNetCrossRefzbMATHGoogle Scholar
  31. Stiller C, Ro F, Ament Ch (2011) Integration of spatial user–item relations into recommender systems. Int J Inf Soc 3(1):190–196Google Scholar
  32. Tenbrink T (2004) Identifying objects on the basis of spatial contrast: an empirical study, international conference on spatial cognition. Lect Notes Comput Sci 3343:124–146CrossRefGoogle Scholar
  33. Trubka R, Glackin S (2016) Modelling housing typologies for urban redevelopment scenario planning. J Comput Environ Urb Syst 57:199–211CrossRefGoogle Scholar
  34. Tychogiorgos G, Bisdikian Ch (2011) Selecting relevant sensor providers for meeting “your” quality information needs. In: Proceedings IEEE conference on mobile data management (MDM), 2011, Lulea, SwedenGoogle Scholar
  35. Wang Sh, Liu D, Liu J, Wang X (2008) An algebra for moving objects. Advances in spatio-temporal analysis. Taylor & Francis Group, London, pp 111–122Google Scholar
  36. Xu Z, Chen L, Chen G (2015) Topic based context-aware travel recommendation method exploiting geotagged photos. Neurocomputing 155:99–107CrossRefGoogle Scholar
  37. Xuan K, Zhao G, Taniar D, Rahayu W, Safar M, Srinivasan B (2014) Voronoi-based range and continuous range query processing in mobile databases. J Comput Syst Sci 77(4):637–651MathSciNetCrossRefzbMATHGoogle Scholar
  38. Zadeh L (1975) The concept of a linguistic variable and its application to approximate reasoning—I. Inf Sci 8:199–249MathSciNetCrossRefzbMATHGoogle Scholar
  39. Zhou Sh, Chu ChH, Yu Zh, Kim J (2012) A context-aware reminder system for elders based on fuzzy linguistic approach. Expert Syst Appl 39:9411–9419CrossRefGoogle Scholar
  40. Zhou M, Dong H, Wang FY, Wang Q, Yang X (2016) Modeling and simulation of pedestrian dynamical behavior based on a fuzzy logic approach. Inf Sci 360:112–130CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Najmeh Neysani Samany
    • 1
    Email author
  • Mahmoud Reza Delavar
    • 2
  • Nicholas Chrisman
    • 3
  1. 1.Department of Remote Sensing and GIS, Faculty of GeographyUniversity of TehranTehranIran
  2. 2.Center of Excellence in Geomatics Engineering and Disaster Management, Department of Surveying and Geomatics Engineering, College of EngineeringUniversity of TehranTehranIran
  3. 3.Department of Geomatic ScienceUniversity of LavalQuebecCanada

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