Distributed inferencing with ambient and wearable sensors
Wireless sensor networks enable continuous and reliable data acquisition for real‐time monitoring in a variety of application areas. Due to the large amount of data collected and the potential complexity of emergent patterns, scalable and distributed reasoning is preferable when compared to centrali...
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| Published in | Wireless communications and mobile computing Vol. 12; no. 1; pp. 117 - 131 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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Chichester, UK
John Wiley & Sons, Ltd
01.01.2012
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| Abstract | Wireless sensor networks enable continuous and reliable data acquisition for real‐time monitoring in a variety of application areas. Due to the large amount of data collected and the potential complexity of emergent patterns, scalable and distributed reasoning is preferable when compared to centralised inference as this allows network wide decisions to be reached robustly without specific reliance on particular network components. In this paper, we provide an overview of distributed inference for both wearable and ambient sensing with specific focus on graphical models—illustrating their ability to be mapped to the topology of a physical network. Examples of research conducted by the authors in the use of ambient and wearable sensors are provided, demonstrating the possibility for distributed, real‐time activity monitoring within a home healthcare environment. Copyright © 2010 John Wiley & Sons, Ltd.
Scalable and distributed reasoning is preferable when compared to centralised inference in wireless sensor networks, due to the large amounts of data collected and the complexity of emergent patterns. This allows network wide decisions to be reached robustly without specific reliance on particular network components. In this paper, we provide an overview of distributed inference for both wearable and ambient sensing with specific focus on graphical models ‐ demonstrating a framework for distributed, real‐time activity monitoring within a home healthcare environment. |
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| AbstractList | Wireless sensor networks enable continuous and reliable data acquisition for real‐time monitoring in a variety of application areas. Due to the large amount of data collected and the potential complexity of emergent patterns, scalable and distributed reasoning is preferable when compared to centralised inference as this allows network wide decisions to be reached robustly without specific reliance on particular network components. In this paper, we provide an overview of distributed inference for both wearable and ambient sensing with specific focus on graphical models—illustrating their ability to be mapped to the topology of a physical network. Examples of research conducted by the authors in the use of ambient and wearable sensors are provided, demonstrating the possibility for distributed, real‐time activity monitoring within a home healthcare environment. Copyright © 2010 John Wiley & Sons, Ltd.
Scalable and distributed reasoning is preferable when compared to centralised inference in wireless sensor networks, due to the large amounts of data collected and the complexity of emergent patterns. This allows network wide decisions to be reached robustly without specific reliance on particular network components. In this paper, we provide an overview of distributed inference for both wearable and ambient sensing with specific focus on graphical models ‐ demonstrating a framework for distributed, real‐time activity monitoring within a home healthcare environment. Abstract Wireless sensor networks enable continuous and reliable data acquisition for real‐time monitoring in a variety of application areas. Due to the large amount of data collected and the potential complexity of emergent patterns, scalable and distributed reasoning is preferable when compared to centralised inference as this allows network wide decisions to be reached robustly without specific reliance on particular network components. In this paper, we provide an overview of distributed inference for both wearable and ambient sensing with specific focus on graphical models—illustrating their ability to be mapped to the topology of a physical network. Examples of research conducted by the authors in the use of ambient and wearable sensors are provided, demonstrating the possibility for distributed, real‐time activity monitoring within a home healthcare environment. Copyright © 2010 John Wiley & Sons, Ltd. |
| Author | Yang, Guang-Zhong Thiemjarus, Surapa Atallah, Louis Lo, Benny McIlwraith, Douglas |
| Author_xml | – sequence: 1 givenname: Louis surname: Atallah fullname: Atallah, Louis organization: Department of Computing, Imperial College London, 180 Queens Gate, London, United Kingdom, SW7 2AZ – sequence: 2 givenname: Douglas surname: McIlwraith fullname: McIlwraith, Douglas organization: Department of Computing, Imperial College London, 180 Queens Gate, London, United Kingdom, SW7 2AZ – sequence: 3 givenname: Surapa surname: Thiemjarus fullname: Thiemjarus, Surapa organization: School of Information and Computer Technology, Sirindhorn International Institute of Technology, Thammasat University, Bangkadi Campus, Pathumthani, Thailand, 12000 – sequence: 4 givenname: Benny surname: Lo fullname: Lo, Benny organization: Department of Computing, Imperial College London, 180 Queens Gate, London, United Kingdom, SW7 2AZ – sequence: 5 givenname: Guang-Zhong surname: Yang fullname: Yang, Guang-Zhong email: gzy@doc.ic.ac.uk organization: Department of Computing, Imperial College London, 180 Queens Gate, London, United Kingdom, SW7 2AZ |
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| References | Burges CJC. A tutorial on support vector machines for pattern recognition. Data Min. Knowledge Discovery 1998; 2(2): 121-167, DOI: http://dx.doi.org/10.1023/A:1009715923555 Pearl J. Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 1988. Intille S, Larson K, Munguia Tapia E, et al. Using a live-in laboratory for ubiquitous computing research. Pervasive, 2006; 349-365. Weiss Y, Freeman WT. Correctness of belief propagation in gaussian graphical models of arbitrary topology. Neural Comput. 2001; 13(10): 2173-2200, DOI: http://dx.doi.org/10.1162/089976601750541769 Yang GZ. Body Sensor Networks. Springer-Verlag: New York, Inc., 2006. Atallah L, Aziz O, Lo B, Yang G-Z. Detecting walking gait impairment with an ear-worn sensor. IEEE BSN 2009, 2009; 175-180. Viterbi A. A personal history of the viterbi algorithm. Signal Processing Magazine, IEEE 2006; 23(4): 120-142, DOI: 10.1109/MSP.2006.1657823 Kalman RE. A new approach to linear filtering and prediction problems. Transactions of the ASME-Journal of Basic Engineering 1960; 82(Series D): 35-45. Predd J, Kulkarni S, Poor H. Distributed learning in wireless sensor networks. Signal Processing Magazine, IEEE 2006; 23(4): 56-69, DOI: 10.1109/MSP.2006.1657817 Wark T, Corke P, Sikka P, et al. Transforming agriculture through pervasive wireless sensor networks. IEEE Pervasive Computing 2007; 6(2): 50-57, DOI: http://doi.ieeecomputersociety.org/10.1109/MPRV.2007.47 Johnson D, Maltz D. Dynamic source routing in ad hoc wireless networks. Mobile Computing 1996; 153-181. Alanyali M, Venkatesh S, Savas O, Aeron S. Distributed bayesian hypothesis testing in sensor networks. American Control Conference, 2004. Proceedings of the 2004 June-2 July 2004; vol. 6(6): 5369-5374. Lo B, Atallah L, Aziz O, ElHelw M, Darzi A, Yang G-Z. Real-time pervasive monitoring for postoperative care. Proceedings of BSN07, IFMBE, vol. 1, 2007; 122-127. Bishop CM. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc.: Secaucus, NJ, USA, 2006. Ripley BD, Hjort NL. Pattern Recognition and Neural Networks. Cambridge University Press: New York, NY, USA, 1995. Abowd G, Bobick A, Essa I, Mynatt E, Rogers W. The aware home: developing technologies for successful aging. Workshop held in conjunction with American Association of Artificial Intelligence (AAAI). Proceedings of AAAI Workshop and Automation as a Care Giver, 2002. Atallah L, El Helw M, Pansiot J, Stoyanov J, Wang L, Yang G-Z. Behaviour profiling with ambient and wearable sensing. Proceedings of BSN 07 2007; 133-138. Lam W, Segre A. A distributed learning algorithm for bayesian inference networks. IEEE Transactions on Knowledge and Data Engineering 2002; 14(1): 93-105, DOI: http://dx.doi.org/10.1109/69.979975 Kschischang F, Frey B, Loeliger H. Factor graphs and the sum-product algorithm. IEEE Transactions on Information Theory 2001; 47(2): 498-519. Weiser M. The computer for the 21st century. Scientific American 1991; 265(3): 94-104. Gu D. Distributed EM algorithm for gaussian mixtures in sensor networks. Neural Networks, IEEE Transactions on 2008; 19(7): 1154-1166, DOI: 10.1109/TNN.2008.915110 Tamura T. Biomedical engineering at the forefront in Japan. Engineering in Medicine and Biology Magazine, IEEE 2005; 24(4): 23-. Wang L, Thiemjarus S, Lo B, Yang GZ. Toward a mixed-signal reconfigurable asic for real-time activity recognition. BSN '08: IEEE proceedings of the 5th International Workshop on Wearable and Implantable Body Sensor Networks, 2008. Mouria-beji F. A hierarchical bayesian model for continuous speech recognition. Pattern Recognition Letters 2002; 23(9): 773-781, DOI: 10.1016/S0167-8655(01)00154-4 Brigham EO. The fast Fourier transform and its applications. Prentice-Hall, Inc.: Upper Saddle River, NJ, USA, 1988. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E. Wireless sensor networks: a survey. Computer Networks 2002; 38: 393-422. Diez FJ, Mira J. Distributed inference in bayesian networks. Cybernetics and Systems 1994; 25. Morris S, Paradiso J. Shoe-integrated sensor system for wireless gait analysis and real-time feedback. Proceedings of the 2nd Joint IEEE EMBS and BMES Conference, 2002; 2468-2469. Nowak R. Distributed EM algorithms for density estimation and clustering in sensor networks. Signal Processing, IEEE Transactions on 2003; 51(8): 2245-2253, DOI: 10.1109/TSP.2003.814623 Edwards N, Barnes N, Garner P, Rose DAD. Life-style monitoring for supported independence. BT Technology Journal 2000; 18(1): 64-65, DOI: http://dx.doi.org/10.1023/A:1026561419189 McIlwraith D, Pansiot J, Thiejarus S, Lo B, Yang G-Z. Probabilistic decision level fusion for real-time correlation of ambient and wearable sensors. IEEE BSN 2008 2008. Pearlman MR, Member S, Haas ZJ, Member S. Determining the optimal configuration for the zone routing protocol. IEEE Journal on Selected Areas in Communications 1999; 17: 1395-1414. Coates M. Distributed particle filters for sensor networks. In Proc. of 3nd workshop on Information Processing in Sensor Networks (IPSN), 2004; 99-107. Wang L, Lo B, Yang GZ. Multichannel reflective ppg earpiece sensor with passive motion cancellation. Biomedical Circuits and Systems, IEEE Transactions on 2007; 1(4): 235-241, DOI: 10.1109/TBCAS.2007.910900 Harmon TC, Ambrose RF, Gilbert RM, Fisher JC, Stealey M, Kaiser WJ. High-resolution river hydraulic and water quality characterization using rapidly deployable networked infomechanical systems (nims rd). Environmental Engineering Science 2007; 24(2): 151-159, DOI: 10.1089/ees.2006.0033 Moallemi CC, Roy BV. Consensus propagation. IEEE Transactions on Information Theory 2006; 52: 4753-4766. Ihler AT, Fisher III JW, Moses RL, Willsky AS. Nonparametric belief propagation for self-calibration in sensor networks. IEEE Journal of Selected Areas in Communication 2005; 23(4): 809-819. Martinez K, Hart J, Ong R. Environmental sensor networks. Computer 2004; 37(8): 50-56, DOI: 10.1109/MC.2004.91 Yu L, Wang N, Meng X. Real-time forest fire detection with wireless sensor networks. Wireless Communications, Networking and Mobile Computing, 2005. Proceedings. 2005 International Conference on 2005; 2: 1214-1217, 10.1109/WCNM.2005.1544272 Pansiot J, Stoyanov D, McIlwraith D, Lo B, Yang G-Z. Ambient and Wearable Sensor Fusion for Activity Recognition in Healthcare Monitoring Systems. BSN'07 2007; 208-212. Cetin M, Chen L, Fisher III, JW, et al. Distributed fusion in sensor networks. Signal Processing Magazine, IEEE 2006; 23(4): 42-55, DOI: 10.1109/MSP.2006.1657816 Bandyopadhyay S, Giannella C, Maulik U, Kargupta H, Liu K, Datta S. Clustering distributed data streams in peer-to-peer environments. Information Sciences 2006; 176(14): 1952-1985, DOI: 10.1016/j.ins.2005.11.007 2002; 38 2002; 14 2006; 52 2008; 19 2004; 46 2009 2008 1997 2007 1996 2006; 176 1994; 25 2004; 6 2006 1995 2005 2004 2003 2002 2003; 51 2001; 47 2005; 23 2005; 24 1999 1960; 82 2000; 18 1991; 265 1990 2006; 23 1999; 17 2002; 23 2004; 37 2007; 6 1998; 2 2005; 2 2007; 1 2001; 13 2007; 24 1988 Paskin MA (e_1_2_5_39_2) 2004 e_1_2_5_27_2 Ripley BD (e_1_2_5_64_2) 1995 e_1_2_5_25_2 Wang L (e_1_2_5_63_2) 2008 e_1_2_5_23_2 e_1_2_5_21_2 Pansiot J (e_1_2_5_19_2) 2007 e_1_2_5_65_2 e_1_2_5_29_2 Arora A (e_1_2_5_10_2) 2004 e_1_2_5_61_2 e_1_2_5_40_2 e_1_2_5_13_2 e_1_2_5_59_2 e_1_2_5_9_2 e_1_2_5_15_2 e_1_2_5_36_2 e_1_2_5_57_2 e_1_2_5_7_2 e_1_2_5_34_2 e_1_2_5_55_2 e_1_2_5_5_2 e_1_2_5_32_2 e_1_2_5_53_2 e_1_2_5_3_2 Alanyali M (e_1_2_5_46_2) 2004; 6 e_1_2_5_30_2 e_1_2_5_51_2 Coates M (e_1_2_5_42_2) 2004 e_1_2_5_26_2 e_1_2_5_49_2 e_1_2_5_24_2 e_1_2_5_47_2 Atallah L (e_1_2_5_18_2) 2009 e_1_2_5_22_2 e_1_2_5_45_2 Abowd G (e_1_2_5_11_2) 2002 e_1_2_5_43_2 Atallah L (e_1_2_5_16_2) 2007 Brigham EO (e_1_2_5_58_2) 1988 Paskin M (e_1_2_5_38_2) 2005 e_1_2_5_28_2 e_1_2_5_60_2 e_1_2_5_62_2 e_1_2_5_41_2 Pearl J (e_1_2_5_44_2) 1988 e_1_2_5_14_2 e_1_2_5_37_2 e_1_2_5_35_2 Funiak S (e_1_2_5_48_2) 2006 e_1_2_5_8_2 e_1_2_5_33_2 e_1_2_5_56_2 e_1_2_5_6_2 e_1_2_5_12_2 e_1_2_5_54_2 e_1_2_5_4_2 e_1_2_5_2_2 Morris S (e_1_2_5_17_2) 2002 McIlwraith D (e_1_2_5_20_2) 2008 e_1_2_5_52_2 e_1_2_5_50_2 P R (e_1_2_5_31_2) 2005 |
| References_xml | – start-page: 83 year: 2005 end-page: 87 – volume: 51 start-page: 2245 issue: 8 year: 2003 end-page: 2253 article-title: Distributed EM algorithms for density estimation and clustering in sensor networks publication-title: Signal Processing, IEEE Transactions on – start-page: 349 year: 2006 end-page: 365 article-title: Using a live‐in laboratory for ubiquitous computing research publication-title: Pervasive – year: 2005 – start-page: 133 year: 2007 end-page: 138 article-title: Behaviour profiling with ambient and wearable sensing publication-title: Proceedings of BSN 07 – volume: 23 start-page: 773 issue: 9 year: 2002 end-page: 781 article-title: A hierarchical bayesian model for continuous speech recognition publication-title: Pattern Recognition Letters – start-page: 467 year: 1999 end-page: 475 – start-page: 270 year: 2004 end-page: 283 – volume: 23 start-page: 56 issue: 4 year: 2006 end-page: 69 article-title: Distributed learning in wireless sensor networks publication-title: Signal Processing Magazine, IEEE – year: 1990 – volume: 82 start-page: 35 year: 1960 end-page: 45 article-title: A new approach to linear filtering and prediction problems publication-title: Transactions of the ASME–Journal of Basic Engineering – volume: 37 start-page: 50 issue: 8 year: 2004 end-page: 56 article-title: Environmental sensor networks publication-title: Computer – volume: 23 start-page: 42 issue: 4 year: 2006 end-page: 55 article-title: Distributed fusion in sensor networks publication-title: Signal Processing Magazine, IEEE – volume: 1 start-page: 235 issue: 4 year: 2007 end-page: 241 article-title: Multichannel reflective ppg earpiece sensor with passive motion cancellation publication-title: Biomedical Circuits and Systems, IEEE Transactions on – volume: 17 start-page: 1395 year: 1999 end-page: 1414 article-title: Determining the optimal configuration for the zone routing protocol publication-title: IEEE Journal on Selected Areas in Communications – year: 2002 article-title: The aware home: developing technologies for successful aging publication-title: Workshop held in conjunction with American Association of Artificial Intelligence (AAAI). Proceedings of AAAI Workshop and Automation as a Care Giver – start-page: 197 year: 1997 end-page: 211 – year: 2008 – volume: 25 year: 1994 article-title: Distributed inference in bayesian networks publication-title: Cybernetics and Systems – volume: 24 start-page: 151 issue: 2 year: 2007 end-page: 159 article-title: High‐resolution river hydraulic and water quality characterization using rapidly deployable networked infomechanical systems (nims rd) publication-title: Environmental Engineering Science – start-page: 109 year: 2007 end-page: 118 – volume: 47 start-page: 498 issue: 2 year: 2001 end-page: 519 article-title: Factor graphs and the sum‐product algorithm publication-title: IEEE Transactions on Information Theory – volume: 6 start-page: 50 issue: 2 year: 2007 end-page: 57 article-title: Transforming agriculture through pervasive wireless sensor networks publication-title: IEEE Pervasive Computing – volume: 265 start-page: 94 issue: 3 year: 1991 end-page: 104 article-title: The computer for the 21st century publication-title: Scientific American – year: 2008 article-title: Probabilistic decision level fusion for real‐time correlation of ambient and wearable sensors publication-title: IEEE BSN 2008 – start-page: 99 year: 2004 end-page: 107 article-title: Distributed particle filters for sensor networks publication-title: In Proc. of 3nd workshop on Information Processing in Sensor Networks (IPSN) – start-page: 175 year: 2009 end-page: 180 article-title: Detecting walking gait impairment with an ear‐worn sensor publication-title: IEEE BSN 2009 – start-page: 153 year: 1996 end-page: 181 article-title: Dynamic source routing in ad hoc wireless networks publication-title: Mobile Computing – start-page: 208 year: 2007 end-page: 212 article-title: Ambient and Wearable Sensor Fusion for Activity Recognition in Healthcare Monitoring Systems publication-title: BSN'07 – volume: 2 start-page: 1214 year: 2005 end-page: 1217 article-title: Real‐time forest fire detection with wireless sensor networks publication-title: Wireless Communications, Networking and Mobile Computing, 2005. Proceedings. 2005 International Conference on – volume: 14 start-page: 93 issue: 1 year: 2002 end-page: 105 article-title: A distributed learning algorithm for bayesian inference networks publication-title: IEEE Transactions on Knowledge and Data Engineering – year: 2007 – volume: 19 start-page: 1154 issue: 7 year: 2008 end-page: 1166 article-title: Distributed EM algorithm for gaussian mixtures in sensor networks publication-title: Neural Networks, IEEE Transactions on – year: 2003 – start-page: 2468 year: 2002 end-page: 2469 article-title: Shoe‐integrated sensor system for wireless gait analysis and real‐time feedback publication-title: Proceedings of the 2nd Joint IEEE EMBS and BMES Conference – volume: 24 start-page: 23 issue: 4 year: 2005 article-title: Biomedical engineering at the forefront in Japan publication-title: Engineering in Medicine and Biology Magazine, IEEE – volume: 6 start-page: 5369 issue: 6 year: 2004 end-page: 5374 article-title: Distributed bayesian hypothesis testing in sensor networks publication-title: American Control Conference, 2004. Proceedings of the 2004 – volume: 52 start-page: 4753 year: 2006 end-page: 4766 article-title: Consensus propagation publication-title: IEEE Transactions on Information Theory – start-page: 576 year: 2008 end-page: 585 – start-page: 270 year: 2008 end-page: 274 – start-page: 116 year: 2007 end-page: 121 – volume: 1 start-page: 122 year: 2007 end-page: 127 article-title: Real‐time pervasive monitoring for postoperative care publication-title: Proceedings of BSN07, IFMBE – start-page: 87 year: 2004 – volume: 38 start-page: 393 year: 2002 end-page: 422 article-title: Wireless sensor networks: a survey publication-title: Computer Networks – year: 2008 article-title: Toward a mixed‐signal reconfigurable asic for real‐time activity recognition publication-title: BSN '08: IEEE proceedings of the 5th International Workshop on Wearable and Implantable Body Sensor Networks – volume: 2 start-page: 121 issue: 2 year: 1998 end-page: 167 article-title: A tutorial on support vector machines for pattern recognition publication-title: Data Min. Knowledge Discovery – year: 1988 – volume: 23 start-page: 809 issue: 4 year: 2005 end-page: 819 article-title: Nonparametric belief propagation for self‐calibration in sensor networks publication-title: IEEE Journal of Selected Areas in Communication – year: 2006 – volume: 13 start-page: 2173 issue: 10 year: 2001 end-page: 2200 article-title: Correctness of belief propagation in gaussian graphical models of arbitrary topology publication-title: Neural Comput. – start-page: 8 year: 2005 – year: 1995 – start-page: 436 year: 2004 end-page: 445 – start-page: 270 year: 2003 end-page: 283 – volume: 46 start-page: 605 year: 2004 end-page: 634 – volume: 18 start-page: 64 issue: 1 year: 2000 end-page: 65 article-title: Life‐style monitoring for supported independence publication-title: BT Technology Journal – volume: 23 start-page: 120 issue: 4 year: 2006 end-page: 142 article-title: A personal history of the viterbi algorithm publication-title: Signal Processing Magazine, IEEE – volume: 176 start-page: 1952 issue: 14 year: 2006 end-page: 1985 article-title: Clustering distributed data streams in peer‐to‐peer environments publication-title: Information Sciences – ident: e_1_2_5_41_2 – ident: e_1_2_5_13_2 doi: http://dx.doi.org/10.1023/A:1026561419189 – start-page: 605 volume-title: Computer Networks (Elsevier) year: 2004 ident: e_1_2_5_10_2 contributor: fullname: Arora A – start-page: 175 year: 2009 ident: e_1_2_5_18_2 article-title: Detecting walking gait impairment with an ear‐worn sensor publication-title: IEEE BSN 2009 contributor: fullname: Atallah L – start-page: 8 volume-title: IPSN '05: Proceedings of the 4th international symposium on Information processing in sensor networks year: 2005 ident: e_1_2_5_38_2 contributor: fullname: Paskin M – year: 2002 ident: e_1_2_5_11_2 article-title: The aware home: developing technologies for successful aging publication-title: Workshop held in conjunction with American Association of Artificial Intelligence (AAAI). Proceedings of AAAI Workshop and Automation as a Care Giver contributor: fullname: Abowd G – ident: e_1_2_5_27_2 doi: 10.1007/978-0-387-45528-0 – ident: e_1_2_5_5_2 doi: 10.1109/MC.2004.91 – ident: e_1_2_5_15_2 doi: 10.1007/978-3-540-70994-7_21 – year: 2008 ident: e_1_2_5_20_2 article-title: Probabilistic decision level fusion for real‐time correlation of ambient and wearable sensors publication-title: IEEE BSN 2008 contributor: fullname: McIlwraith D – ident: e_1_2_5_24_2 doi: 10.1109/49.779922 – volume-title: Advances in Neural Information Processing 19 year: 2006 ident: e_1_2_5_48_2 contributor: fullname: Funiak S – ident: e_1_2_5_53_2 doi: 10.1109/TIT.2006.883539 – ident: e_1_2_5_21_2 doi: 10.1109/ICISIP.2005.1529427 – ident: e_1_2_5_55_2 – ident: e_1_2_5_36_2 doi: 10.1109/MSP.2006.1657817 – ident: e_1_2_5_2_2 doi: 10.1038/scientificamerican0991-94 – ident: e_1_2_5_54_2 doi: 10.1109/18.910572 – ident: e_1_2_5_57_2 doi: 10.1115/1.3662552 – ident: e_1_2_5_26_2 – ident: e_1_2_5_37_2 doi: http://dx.doi.org/10.1109/69.979975 – ident: e_1_2_5_40_2 doi: 10.1109/MSP.2006.1657816 – ident: e_1_2_5_56_2 doi: 10.1109/MSP.2006.1657823 – volume-title: Pattern Recognition and Neural Networks year: 1995 ident: e_1_2_5_64_2 contributor: fullname: Ripley BD – start-page: 2468 year: 2002 ident: e_1_2_5_17_2 article-title: Shoe‐integrated sensor system for wireless gait analysis and real‐time feedback publication-title: Proceedings of the 2nd Joint IEEE EMBS and BMES Conference contributor: fullname: Morris S – ident: e_1_2_5_22_2 doi: 10.1007/978-0-585-29603-6_5 – ident: e_1_2_5_23_2 doi: 10.17487/rfc3561 – ident: e_1_2_5_14_2 doi: 10.1109/MEMB.2005.1463391 – start-page: 99 year: 2004 ident: e_1_2_5_42_2 article-title: Distributed particle filters for sensor networks publication-title: In Proc. of 3nd workshop on Information Processing in Sensor Networks (IPSN) contributor: fullname: Coates M – start-page: 436 volume-title: AUAI '04: Proceedings of the 20th conference on Uncertainty in artificial intelligence year: 2004 ident: e_1_2_5_39_2 contributor: fullname: Paskin MA – ident: e_1_2_5_3_2 doi: 10.1007/1-84628-484-8 – ident: e_1_2_5_4_2 doi: 10.1016/S1389-1286(01)00302-4 – ident: e_1_2_5_43_2 doi: 10.1145/1236360.1236375 – start-page: 133 year: 2007 ident: e_1_2_5_16_2 article-title: Behaviour profiling with ambient and wearable sensing publication-title: Proceedings of BSN 07 contributor: fullname: Atallah L – ident: e_1_2_5_62_2 doi: 10.1109/PCTHEALTH.2008.4571011 – ident: e_1_2_5_28_2 doi: http://dx.doi.org/10.1023/A:1009715923555 – ident: e_1_2_5_50_2 doi: http://dx.doi.org/10.1162/089976601750541769 – ident: e_1_2_5_61_2 doi: 10.1109/ITAB.2008.4570518 – volume-title: The fast Fourier transform and its applications year: 1988 ident: e_1_2_5_58_2 contributor: fullname: Brigham EO – ident: e_1_2_5_6_2 doi: 10.1109/MPRV.2007.47 – ident: e_1_2_5_49_2 – ident: e_1_2_5_52_2 doi: 10.1145/1015330.1015403 – volume: 6 start-page: 5369 issue: 6 year: 2004 ident: e_1_2_5_46_2 article-title: Distributed bayesian hypothesis testing in sensor networks publication-title: American Control Conference, 2004. Proceedings of the 2004 doi: 10.23919/ACC.2004.1384706 contributor: fullname: Alanyali M – ident: e_1_2_5_35_2 doi: 10.1109/TNN.2008.915110 – ident: e_1_2_5_51_2 – year: 2008 ident: e_1_2_5_63_2 article-title: Toward a mixed‐signal reconfigurable asic for real‐time activity recognition publication-title: BSN '08: IEEE proceedings of the 5th International Workshop on Wearable and Implantable Body Sensor Networks contributor: fullname: Wang L – ident: e_1_2_5_65_2 doi: 10.1109/TBCAS.2007.910900 – ident: e_1_2_5_8_2 doi: 10.1089/ees.2006.0033 – volume-title: Probabilistic reasoning in intelligent systems: networks of plausible inference year: 1988 ident: e_1_2_5_44_2 contributor: fullname: Pearl J – start-page: 208 year: 2007 ident: e_1_2_5_19_2 article-title: Ambient and Wearable Sensor Fusion for Activity Recognition in Healthcare Monitoring Systems publication-title: BSN'07 contributor: fullname: Pansiot J – ident: e_1_2_5_45_2 doi: 10.1080/01969729408902314 – ident: e_1_2_5_9_2 doi: 10.1145/990064.990096 – ident: e_1_2_5_12_2 doi: 10.1007/11748625_22 – ident: e_1_2_5_34_2 doi: 10.1016/j.ins.2005.11.007 – ident: e_1_2_5_33_2 doi: 10.1109/TSP.2003.814623 – ident: e_1_2_5_47_2 doi: 10.1109/JSAC.2005.843548 – ident: e_1_2_5_60_2 – ident: e_1_2_5_7_2 doi: 10.1109/WCNM.2005.1544272 – ident: e_1_2_5_29_2 doi: http://dx.doi.org/10.1109/SWOD.2007.353208 – ident: e_1_2_5_59_2 doi: 10.4108/bodynets.2007.1009 – ident: e_1_2_5_25_2 – ident: e_1_2_5_32_2 doi: 10.1016/S0167‐8655(01)00154‐4 – ident: e_1_2_5_30_2 doi: http://dx.doi.org/10.1007/978‐3‐540‐69158‐7_60 – volume-title: Advance Neural Information Processing Systems (NIPS '04) year: 2005 ident: e_1_2_5_31_2 contributor: fullname: P R |
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| Snippet | Wireless sensor networks enable continuous and reliable data acquisition for real‐time monitoring in a variety of application areas. Due to the large amount of... Abstract Wireless sensor networks enable continuous and reliable data acquisition for real‐time monitoring in a variety of application areas. Due to the large... |
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| SubjectTerms | ambient sensing Bayesian networks body sensor networks distributed inference factor graphs inference wearable sensing |
| Title | Distributed inferencing with ambient and wearable sensors |
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