Abstract
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.
Similar content being viewed by others
References
Alegre U, Carlos Augusto J, Clark T (2016) Engineering context-aware systems and applications: a survey. J Syst Softw 117:55–83
Allen JF (1983) Maintaining knowledge about temporal intervals. J. Commun ACM 26(11):832–843
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 48–53
Bobek S, Nalepa GJ (2017) Uncertainty handling in rule-based mobile context-aware systems. Pervas Mob Comput 39:159–179
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 94–115
Cadenas JT, Marín N, Vila MA (2014) Context-aware fuzzy databases. J Appl Soft Comput 25:215–233
Choi D, Kim N, Tuan Hung D (2012) Conceptual data modeling for realizing context-aware services. J Expert Syst Appl 39:3022–3030
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 97–134
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 12:301–313
Gebbert S, Pebesma E (2014) A temporal GIS for field based environmental modeling. J Environ Model Softw 53:1–12
Golumbic MC, Shamir R (1993) Complexity and algorithms for reasoning about time: a graph theoretic approach. J ACM 40(5):1128–1133
González JA, Rodríguez-Cortés FJ, Cronie O, Mateua J (2016) Spatio-temporal point process statistics: a review. J Spat Stat 18:505–544
Holzmann C, Ferscha A (2010) A framework for utilizing qualitative spatial relations between networked embedded systems. J Pervas Mob Comput 6:362–381
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 36:7448–7457
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 24:1446–1460
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 169:236–245
Lee J, Chang HL, Kim DW, Kang BY (2017) Smartphone-assisted pronunciation learning technique for ambient intelligence. IEEE Access 5(99):312–325
Lim BY, Dey AK (2009) Assessing demand for intelligibility in context-aware applications. UbiComp2009, Sep 30–Oct 3, Orlando, Florida, USA, pp 195–254
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):1–8
Mamdani EH (1977) Applications of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26(12):1182–1191
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 256
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:271–282
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 9:189–208
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 33:116–126
Olsson T, Kakkainen T, Lagerstam E, Venta- Olkonen L (2012) User evaluation of mobile augmented reality scenarios. J Amb Intel Smart Environ 4:29–47
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):1497–1515
Reichenbacher T (2005) The concept of relevance in mobile maps. Location based services and tele-cartography. Lect Notes Geo-Inf Cartogr Section III:231–246
Renz J, Schmid F (2007) Customizing qualitative spatial and temporal calculi. In: Orgun MA, Thornton J (eds) AI, vol LNAI 4830. Springer, Berlin, pp 293–304
Salton G, McGill M (1984) Introduction to modern information retrieval. McGraw-Hill, New York
Schockaert S, Cock MD (2008) Temporal reasoning about fuzzy intervals. J Artif Intell 172:1158–1193
Stiller C, Ro F, Ament Ch (2011) Integration of spatial user–item relations into recommender systems. Int J Inf Soc 3(1):190–196
Tenbrink T (2004) Identifying objects on the basis of spatial contrast: an empirical study, international conference on spatial cognition. Lect Notes Comput Sci 3343:124–146
Trubka R, Glackin S (2016) Modelling housing typologies for urban redevelopment scenario planning. J Comput Environ Urb Syst 57:199–211
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, Sweden
Wang Sh, Liu D, Liu J, Wang X (2008) An algebra for moving objects. Advances in spatio-temporal analysis. Taylor & Francis Group, London, pp 111–122
Xu Z, Chen L, Chen G (2015) Topic based context-aware travel recommendation method exploiting geotagged photos. Neurocomputing 155:99–107
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):637–651
Zadeh L (1975) The concept of a linguistic variable and its application to approximate reasoning—I. Inf Sci 8:199–249
Zhou Sh, Chu ChH, Yu Zh, Kim J (2012) A context-aware reminder system for elders based on fuzzy linguistic approach. Expert Syst Appl 39:9411–9419
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 360:112–130
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Samany, N.N., Delavar, M.R. & Chrisman, N. Developing FIA5 to FSTPR25 for modeling spatio-temporal relevancy in context-aware wayfinding systems. J Ambient Intell Human Comput 11, 2453–2466 (2020). https://doi.org/10.1007/s12652-019-01287-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-019-01287-1