A Versatile Lattice Based Model For Situation Recognition From Dynamic Ambient Sensors
By:
References
- S.Katz et al, “Progress in development of the index of ADL”,The Gerontologist, pp 20-30Vol. 10, Issue 1,1970.
- T.Gu, L.Wang, W. Zhanqing,T. Xianping and L. Jian,”A pattern mining approach to sensorbased human activity recognition”, IEEE Transactions on Knowledge and Data Engineering, pp 1359-1372, Vol. 23, Issue 9, September 2011.
- D.Guan, T.Ma,W.Yuan, Y. Lee, AM JehadSarkar, “Review of Sensor-based Activity Recognition Systems”, pp. 418-33 Vol. 28, Issue 5, IETE Tech Rev,Oct 2011.
- A. Bauer and Y. Fischer, “Task-oriented Situation Recognition”, In Proc. of Cyber Security, Situation Management and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II, SPIE Vol. 7709,2010.
- J. Ye, S. Dobson and S. McKeever, “Situation Identification Techniques in Pervasive Computing: A Review”, Pervasive Mobile Computing, pp 36-66, Vol. 8, Issue 1, February 2012.
- A. Dahlbom, L. Niklasson,G. Falkman and A. Loutfi, “Towards Template-Based Situation Recognition,” in Proc. of Intelligent Sensing, Situation Management, Impact Assessment and Cyber-Sensing, SPIE Vol. 7352, 2009.
- C Carpineto, G Romano, “Concept Data Analysis: Theory and Applications”, John Wiley, 2004.
- T VKasteren, G Englebienne and B Kröse, “Transferring Knowledge of Activity Recognition Across Sensor Networks”, In Proceedings of the 8th international conference on Pervasive Computing, pp 283-300, 2010.
- S Mittal and S L Maskara, “A Review of Bayesian Belief Network Structure Learning Algorithms”, In Proceedings of 8th International Conference on Information, Communications and Signal Processing (ICICS), 13 -16 Dec, Singapore.
- S Mittal, AAggarwal, S L Maskara, “Application of Bayesian Belief Networks for Context Extraction from Wireless Sensors Data”, 14th International Conference on Advanced Communication Technology (ICACT2012), pp 410 -415, Korea, 2012.
- R Cardell-Oliver and Liu Wei, “Representation and Recognition of Situations in Sensor Networks,” IEEE Communications Magazine, Vol.48, Issue 3, pp.112-117, March 2010.
- Y Oh, J Han and W Woo, “A context management architecture for large-scale smart environments,” IEEE Communications Magazine, Vol. 48, Issue 3, March 2010
- A. Dahlbom, L. Niklasson, G. Falkman and A. Loutfi, “Towards template-based situation recognition,” in Proceedings of SPIE on Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing, Vol. 7352. 2009.
- J Ye, L Coyle, S Dobson and P Nixon, “Representing and manipulating situation hierarchies using situation lattices,”Revue d’intelligenceartificielle, Vol. 22, Issue 5, pp 647-667, 2008.
- K. Thirunarayan, C. Henson and A. Sheth, “Situation awareness via Abductive Reasoning from Semantic Sensor data: A preliminary report,” International Symposium on Collaborative Technologies and Systems, pp.111-118, May 2009.
- A Srivastav, W Yicheng, E Hendrick,I Chattopadhyay, A Ray and S Phoha,”Information Fusion for Object &Situation Assessment in Sensor Networks,” In Proceedings ofAmerican Control Conference (ACC), pp.1274-1279, 2011.
- Lu-An Tang, Yu Xiao, Kim Sangkyum et al., “Multidimensional Sensor Data Analysis in Cyber-Physical System: An Atypical Cube Approach,” International Journal of Distributed Sensor Networks, Vol. 2012, Article ID 724846, 19 pages, 2012.
- J Fogarty and S E. Hudson, “Toolkit Support for Developing and Deploying Sensor-Based Statistical Models of Human Situations”, In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp 135-144, 2007, ACM, New York,USA.
- S. Yau, D. Huang, H. Gong andY. Yao, “Support for Situation Awareness in Trustworthy UbiquitousComputing Application Software,” Software: Practice and Experience, pp 893-921, Vol. 36, No. 9,2006.
- P. Costa, G. Guizzardi, J. Almeida, L. Pires and M. Van Sinderen, “Situations inConceptual Modeling of Context,”In Proceedings of the 10th IEEE International Enterprise Distributed Object Computing Conference Workshops, pp 6-16, October, 2006.Hong Kong.
- S. W. Loke, “Representing and Reasoning with Situations for Context-Aware Pervasive Computing: ALogic Programming Perspective”, Knowledge Engineering Review, pp 213-233, Vol. 19 Issue 3, 2004.
- G. Thomson, S.Terzis and P. Nixon, “Situation Determination with Reusable Situation Specifications,” InProceedings of 4th IEEE International Conference on Pervasive Computing and Communications, pp 620-623, March 2006.
- T. Emmanuel, S. Intille and K. Larson, “Activity Recognition in the Home Using Simple and Ubiquitous Sensors”, In Proceedings of 2nd International Conference on Pervasive Computing in LNCS, Springer, Vol. 3001, pp 158-175,2004.
- N. Bicocchi, M. Lasagni andF. Zambonelli, “Bridging Vision and Commonsense forMultimodal Situation Recognition in Pervasive Systems,” 12thIEEE International Conference on Pervasive Computing and Communications,pp48-56, March 2012.
- L. Atallah et al., “Distributed Inferencing with Ambient and Wearable Sensors”, Wireless Communications and Mobile Computing, pp 117-131, Vol. 12, Issue 1, 2010.
- Y. Fischer, A. Bauer and J.Beyerer, “A Conceptual Framework for Automatic Situation Assessment,” in Proceedings of First International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), pp.234-239, 2011.
- A. Mahajan, C. Oesch, H. Padmanaban, L. Utterback, S. Chitikeshi and F. Figueroa, “Physical and Virtual Intelligent Sensors for Integrated Health Management Systems”, International Journal on Smart Sensing and Intelligent Systems, pp 559 – 575, Vol. 5, No. 3, September 2012.
- B.Ganter and R.Wille, “Formal Concept Analysis: Mathematical Foundations”, Springer Verlag, 1999.
- K. Dalkir, “Knowledge Management in Theory and Practice”, The MITPress, 2011.
- http://conexp.sourceforge.net/
- J. Poelmans et al., “Formal Concept Analysis in Knowledge Discovery: ASurvey”, In Proceedings of 18th International Conference on Conceptual Structures: From Information to Intelligence,pp 139-153, 2010.
- J. Herethet al.,”Conceptual Knowledge Discovery and Data Analysis”, In Proceedings of 8th International Conference onConceptual Structures: Logical, Linguistic, and Computational Issues, pp 421-437, 2000.
- Y. Zhao, K. George and U. Fayyad, “Hierarchical Clustering Algorithms for Document Datasets”, Data Mining and Knowledge Discovery, pp 141-168, Vol.10, Issue 2, March 2005.
- A. Mannini and A. Sabatini, “Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers”, Sensors,pp. 1154-1175,Vol. 10,Issue 2, February 2010.
DOI: https://doi.org/10.21307/ijssis-2017-547 | Journal eISSN: 1178-5608
Language: English
Page range: 403 - 432
Submitted on: Oct 9, 2012
Accepted on: Feb 10, 2013
Published on: Feb 20, 2013
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year
Keywords:
Related subjects:
© 2013 Sangeeta Mittal, Krishna Gopal, S.L. Maskara, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.