請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/62730
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 朱浩華 | |
dc.contributor.author | Tsung-Te Lai | en |
dc.contributor.author | 賴宗德 | zh_TW |
dc.date.accessioned | 2021-06-16T16:08:42Z | - |
dc.date.available | 2013-06-21 | |
dc.date.copyright | 2013-06-21 | |
dc.date.issued | 2013 | |
dc.date.submitted | 2013-05-03 | |
dc.identifier.citation | Bibliography
[1] I. Stoianov, L. Nachman, S. Madden and T. Tokmouline. PIPENET: A Wireless Sensor network for pipeline monitoring. In Proceedings of the International Conference on Information Processing in Sensor Networks, 2007 [2] Y. Kim, T. Schmid, Z. M. Charbiwala, J. Friedman and M. B. Srivastava. NAWMS: Non-Intrusive Autonomous Water Monitoring System. In Proceedings of the ACM Conference on Embedded Network Sensor Systems, 2008 [3] J. Froehlich, E. Larson, T. Campbell, C. Haggerty, J. Fogarty, and S.N. Patel. HydroSense: Infrastructure- Mediated Single-Point Sensing of Whole-Home Water Activity. In Proceedings of the International Conference on Ubiquitous Computing, 2009 [4] S. Srirangaragan, M. Allen, A. Preis, M. Iqbal, H. B. Lim and A. J. Whittle. Water main burst event detection and localization. In Proceedings of 12th Water Distribution Systems Analysis Conference, 2010 [5] O. Gnawali, R. Fonseca, K. Jamieson, D. Moss and P. Levis. Collection Tree Protocol. In Proceedings of the ACM Conference on Embedded Network Sensor Systems, 2009 [6] Kmote, INTECH http://www.tinyosmall.com/product_p/100-101.htm [7] PQ12-P Linear Actuator, Firgelli. http://store.firgelli.com/pq12-p-linear-actuato12.html [8] G. Barrenetxea, F. Ingelrest, G. Schaefer and M. Vetterli. The hitchhiker's guide to successful wireless sensor network deployments. In Proceedings of the ACM Conference on Embedded Network Sensor Systems, 2008 [9] A. Krause, C. Guestrin, A. Gupta, and J. Kleinberg. Near-optimal Sensor Placements: Maximizing Information while Minimizing Communication Cost. In Proceedings of the International Conference on Information Processing in Sensor Networks, 2006 [10] K. Ni, N. Ramanathan, M. N. H. Chehade, L. Balzano, S. Nair, S. Zahedi, E. Kohler, G. Pottie, M. Hansen and M. Srivastava. Sensor Network Data Fault Types. ACM Transactions on Sensor Networks, Vol. 5, No. 3, Article 25, May 2009 [11] M. Ceriotti, M. Corra, L. D'Orazio, R. Doriguzzi, D. Facchin, S. T. Guna, G. P. Jesi, R. L. Cigno, L. Mottola, A. L. Murphy, M. Pescalli, G. P. Picco, D. Pregnolato and C. Torghele. Is there light at the ends of the tunnel? Wireless sensor networks for adaptive lighting in road tunnels. In Proceedings of the International Conference on Information Processing in Sensor Networks, 2011 [12] I. Vasilescu, K. Kotay, D. Rus, M. Dunbabin and P. Corke. Data collection, storage, and retrieval with an underwater sensor network. In Proceedings of the ACM Conference on Embedded Network Sensor Systems, 2005 [13] G. Chen, S. Hanson, D. Blaauw and D. Sylvester. Circuit Design Advances for Wireless Sensing Applications. Proceedings of the IEEE, Vol.98, No.11, pp.1808-1827, Nov. 2010 [14] Y. C. Wang, C. C. Hu and Y. C. Tseng. Efficient Placement and Dispatch of Sensors in a Wireless Sensor Network. IEEE Transactions on Mobile Computing, Vol. 7, No. 2. pp. 262-274, Feb. 2008 [15] M. Laibowitz and J. A. Paradiso. Parasitic mobility for Proceedings of the International Conference on Pervasive Computing sensor networks. In Proceedings of the International Conference on Pervasive Computing, 2005 [16] K. Dantu, B. Kate, J. Waterman, P. Bailis and M. Welsh. Programming Micro-aerial vehicle swarms with Karma. In Proceedings of the ACM Conference on Embedded Network Sensor Systems, 2011 [17] T. Bourdenas, M. Sloman and E. C. Lupu. Self-healing for Pervasive Computing Systems. Architecting Dependable Systems VII, Springer-Verlag, 2010 [18] A. Purohit, Z. Sun, F. Mokaya and P. Zhang. SensorFly: Controlled-mobile Sensing Platform for Indoor Emergency Response Applications. In Proceedings of the International Conference on Information Processing in Sensor Networks, 2011 [19] S. Guo, Z. Zhong and T. He. FIND: faulty node detection for wireless sensor networks. In Proceedings of the ACM Conference on Embedded Network Sensor Systems, 2009 [20] H. Liu, J. Li, Z. Xie, S. Lin, K. Whitehouse, J. A. Stankovic and D. Siu. Automatic and Robust Breadcrumb System Deployment for Indoor Firefighter Applications. In Proceedings of the International Conference on Mobile Systems, Applications, and Services, 2010 [21] MS5541C Pressure Sensor http://www.intersema.ch/products/guide/calibrated/ms5541 [22] The STMicroelectronics LISY300AL gyroscope chip http://www.st.com/stonline/books/pdf/docs/14753.pdf [23] C. Park and P.H. Chou, Eco: Ultra-Wearable and Expandable Wireless Sensor Platform. In Proceedings of the International Workshop on Body Sensor Network, 2006 [24] J. Fogarty, C. Au and S. E. Hudson. Sensing from the basement: A feasibility study of unobtrusive and low-cost home activity recognition. In Proceedings of the Annual ACM Symposium on User Interface Software and Technology, 2006 [25] P. V. Alvarado and K. Youcef-Toumi. Performance of Machines with Flexible Bodies Designed for Biomimetic Locomotion in Liquid Environments. In Proceedings of the IEEE International Conference on Robotics and Automation, 2005 [26] PPFA (Plastic Pipe and Fittings Association), Design Guide, Residential PEX Water Supply Plumbing Systems (2006), http://www.toolbase.org/PDF/DesignGuides/pex_designguide.pdf [27] American Society of Home Inspectors, http://www.ashi.org/media/press/ [28] C. Dump. Principles of Home Inspection: Plumbing. Dearborn Home Inspection Education, 2003 [29] AWWARF (American Water Works Association Research Foundation). 1999. Residential end uses of water study. http://www.allianceforwaterefficiency.org/residential-end-uses-of-water-study-1999.aspx [30] T. Campbell, E. Larson, G. Cohn, J. Froehlich, R. Alcaide and S. N. Patel. WATTR: A nethod for self-powered wireless sensing of water activity in the home. In Proceedings of the International Conference on Ubiquitous Computing, 2010 [31] Y. A. Cengel and J. M. Cimbala. Fluid Mechanics, 2005 [32] I. Constandache, R. R. Choudhury, and I. Rhee. Towards mobile phone localization without war-driving. In Proceedings of IEEE International Conference on Computer Communications, 2010 [33] S.B. Eisenman, E. Miluzzo, N.D. Lane, R.A. Peterson, G.-S. Ahn and A.T. Campbell. BikeNet: A mobile sensing system for cyclist experience mapping. ACM Transactions on Sensor Networks. Vol. 6, No. 1, Article 6. 2010 [34] R.P. Evans, J.D. Blotter and A. Stephens. Flow rate measurements using flow-induced pipe vibration. Journal of Fluids Engineering, 2004 [35] J. Froehlich, E. Larson, E. Saba, T. Campbell, L. Atlas, J. Fogarty and S. N. Patel. A longitudinal study of pressure sensing to infer real-world water usage events in the home. In Proceedings of the International Conference on Pervasive Computing, 2011 [36] C. Jekeli. Inertial Navigation Systems with Geodetic Applications. Walter de Gruyter, 2000 [37] J. Kim, J. S. Lim, J. Friedman, U. Lee, L. Vieira, D. Rosso, M. Gerla and M. B. Srivastava. 2009. SewerSnort: a drifting sensor for in-situ sewer gas monitoring. In Proceedings of Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 2009 [38] NPS (Nominal Pipe Size). http://en.wikipedia.org/wiki/Nominal_Pipe_Size [39] D.B. Pervical and A.T. Walden. Wavelet Methods for Time Series Analysis. Cambridge University Press, 2000 [40] Radiodetection. http://www.radiodetection.com [41] K. Srinivasan, P.l Dutta, A. Tavakoli, P. Levis. An Empirical Study of Low Power Wireless. ACM Transactions on Sensor Networks, Vol. 6, No. 2, Article 16, Mebruary 2010 [42] A.B.M. Musa and J. Eriksson. Passive Smartphone Tracking Using Wi-Fi Monitors. In Proceedings of International Conference on Embedded Networked Sensor Systems, 2012 [43] J. Biagioni, T. Gerlich, T. Merrifield, and J. Eriksson. EasyTracker: Automatic Transit Tracking, Mapping, and Arrival Time Prediction Using Smartphones. In Proceedings of International Conference on Embedded Networked Sensor Systems, 2011 [44] SmartBall, Pure Technologies http://www.puretechltd.com/products/smartball/smartball_lea k_detection.shtml [45] ROBOBEES project http://robobees.seas.harvard.edu [46] L. Girod, M. Lukac, V. Trifa, and D. Estrin. The design and implementation of a self-calibrating acoustic sensing platform. In Proceedings of International Conference on Embedded Networked Sensor Systems, 2006 [47] P. Bahl and V. Padmanabhan. RADAR: an in-building RF-based user location and tracking system. In Proceedings of 19th IEEE International Conference on Computer Communications, 2000 [48] H.L. Chang, J.B. Tian, T.T. Lai, H.H. Chu, P. Huang. Spinning Beacons for Precise Indoor Localization. In Proceedings of International Conference on Embedded Networked Sensor Systems, 2008 [49] T. He, C. Huang, B. M. Blum, J. A. Stankovic, and T. Abdelzaher. Range-free localization schemes in large-scale sensor networks. In Proceedings of International Conference on Mobile Computing and Networking, 2003 [50] R. Stoleru, T. He, J. A. Stankovic, and D. Luebke. A high-accuracy, low-cost localization system for wireless sensor networks. In Proceedings of International Conference on Embedded Networked Sensor Systems, 2005 [51] K. R‥omer. The lighthouse location system for smart dust. In Proceedings of International Conference on Mobile Systems, Applications, and Services, 2003 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/62730 | - |
dc.description.abstract | An important problem in wireless sensor networks (WSNs) is how to scale down the amount of human effort in deploying and maintaining a WSN infrastructure. This is because human effort often hinders the successful long-term deployment of a WSN. Placing new sensors and replacing existing sensors often require humans to go on-site. The cost of this human effort can be prohibitive when a WSN is deployed in the wild.
This dissertation introduces the concept of a single-release point sensing method for mobile sensors with the aim of reducing to reduce the human effort required to deploy and maintain a WSN infrastructure. This single-release point sensing method enables the automated deployment of mobile sensors and the automated replacement of battery-depleted (or faulty) sensors. This dissertation demonstrates the feasibility and benefits of single-release point sensing by developing two successive systems for pipeline monitoring applications. First, we designed and implemented PipeProbe, which is a mobile sensor system for mapping the 3D spatial topology of hidden water pipelines behind walls. PipeProbe works by releasing a sensor node from a single point of water inlet. The flowing water carries the node through the entire pipeline infrastructure. By gathering data from a water pressure sensor, 3D accelerometer, and 3D gyroscope, PipeProbe can reconstruct the hidden layout of the pipeline. However, human effort is required to release sensor at the single point of water inlet and retrieve the sensor at the water outlet. Second, we designed and implemented TriopusNet, which is a system that automates WSN deployment and replacement in pipeline monitoring. This system works by releasing multiple sensor nodes from a single water inlet until the nodes cover the entire pipeline. Each node in TriopusNet consists of a latching mechanism that allows the nodes to automatically latch themselves inside the pipeline. This study also presents a placement algorithm to determine when and where to place sensors, and designs a replacement algorithm to replace the nodes when the node runs out of battery. These hardware prototype and algorithms can dramatically reduce the human effort required by pipeline monitoring. Finally, we extensively evaluated the proposed systems by building a real testbed and conducting real test scenarios to determine the feasibility of the single-release point sensing method. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T16:08:42Z (GMT). No. of bitstreams: 1 ntu-102-F96922152-1.pdf: 1752249 bytes, checksum: b9561e8e90df16aa3c15134b9cebe4d0 (MD5) Previous issue date: 2013 | en |
dc.description.tableofcontents | Content
Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Dissertation Contributions 3 1.3 Dissertation Outline 4 Chapter 2. Piprprobe: Mapping Hidden Water Pipelines using a Mobile Sensor Droplet 5 2.1 Motivation 6 2.2 Pipeline Profiling and Single-Release Point Sensing 8 2.2.1 Vertical Movement 9 2.2.2 Horizontal Movement 10 2.3 Data Collection 11 2.4 Data Processing 15 2.4.1 Appling a Median Filter to Pressure Readings 16 2.4.2 Turn Detection 18 2.4.2.1 V-Turn Detection 20 2.4.2.2 H-Turn Detection 23 2.4.3 Layout Mapping 27 2.4.4 Ambiguity Elimination 30 2.5 Testbed 31 2.6 Evaluation 34 2.6.1 Length Errors 35 2.6.2 Positional Errors 38 2.6.3 Sampling Rate 39 2.6.4 Data Collection Trips 41 2.7 Detect Variable-Diameter Pipes and 45-degree bends 42 2.7.1 Variable-Diameter Pipes 42 2.7.2 Detecting 45-Degree Bends 49 2.7.2.1 Detecting 45-Degree Vertical Bends 49 2.7.2.2 Detecting 45-Degree Horizontal Bends 51 Chapter 3. TriopusNet: Automating Wireless Sensor Network Deployment and Replacement in Pipeline Monitoring 54 3.1 Motivation 54 3.2 System overview, Assumptions, and Limitations 59 3.3 Hardware Design 63 3.4 System Design 66 3.4.1 Sensor Deployment Order 66 3.4.2 Sensor Deployment 68 3.4.3 Sensor Movement 69 3.4.4 Sensor Localization 69 3.4.5 Sensor Latching 70 3.4.6 Data Collection 71 3.4.7 Sensor Replacement 71 3.5 Experimental Design 73 3.5.1 Experimental Testbed 73 3.5.2 Performance Metrics 74 3.5.3 Experimental Procedure 75 3.6 Experiment Results 76 3.6.1 Results for Automated Sensor Deployment 76 3.6.1.1 Node Locations 77 3.6.1.2 Data Collection Rate (DCR) 79 3.6.1.3 Positional Accuracy 80 3.6.1.4 Time to Deployment 81 3.6.1.5 Energy Consumption 81 3.6.2 Results for Automated Sensor Replacement 82 3.6.2.1 Data Collection Rate 83 3.6.2.2 Time to Replacement 83 Chapter 4. Discussion and Limitations 85 4.1 PipeProbe Limitataions and Future Extensions 85 4.2 TriopusNet Limitataions and Future Extensions 87 Chapter 5. Related Work 89 5.1 Mobile WSN Deployment 89 5.2 WSN in Pipeline Monitoring 90 5.3 Pipeline Layout Mapping 92 5.4 Sensor Mobility 92 5.5 Sensor Localization 93 Chapter 6. Conclusion and Future Work 96 Bibliography 99 | |
dc.language.iso | en | |
dc.title | 以單一節點釋放的感測 | zh_TW |
dc.title | Single-Release Point Sensing | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-2 | |
dc.description.degree | 博士 | |
dc.contributor.coadvisor | 黃寶儀 | |
dc.contributor.oralexamcommittee | 周百祥,張韻詩,許永真,陳銘憲 | |
dc.subject.keyword | 無線感測網路, | zh_TW |
dc.subject.keyword | wireless sensor network, | en |
dc.relation.page | 105 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2013-05-03 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-102-1.pdf 目前未授權公開取用 | 1.71 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。