Abstract
Pervasive applications rely on data captured from the physical world through sensor devices. Data provided by these devices, however, tend to be unreliable. The data must, therefore, be cleaned before an application can make use of them, leading to additional complexity for application development and deployment. Here we present Extensible Sensor stream Processing (ESP), a framework for building sensor data cleaning infrastructures for use in pervasive applications. ESP is designed as a pipeline using declarative cleaning mechanisms based on spatial and temporal characteristics of sensor data. We demonstrate ESP’s effectiveness and ease of use through three real-world scenarios.
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References
Alien Technology. Nanoscanner Reader User Guide
Alien Technology. Personal correspondence
MIT House_n, http://architecture.mit.edu/house_n/
Abadi, D., et al.: Aurora: a data stream management system. In: SIGMOD (2003)
Alien ALL-9250 I2 RFID tag, http://www.alientechnology.com/products/rfid-tags
Alien ALR-9780 915 MHz RFID Reader, http://www.alientechnology.com/products/rfid-readers/alr9780.php
Application Level Event (ALE) Specification Version 1.0, http://www.epcglobalinc.org/standards_technology/EPCglobal_ApplicationALE_Specification_v112-2005.pdf
Arasu, A., et al.: The CQL continuous query language: Semantic foundations and query execution. VLDB Journal (to appear)
Babcock, B., et al.: Models and issues in data stream systems. In: SIGMOD (2002)
Bonnet, P., Gehrke, J., Seshadri, P.: Towards sensor database systems. In: Tan, K.-L., Franklin, M.J., Lui, J.C.-S. (eds.) MDM 2001. LNCS, vol. 1987, pp. 3–14. Springer, Heidelberg (2000)
Buonadonna, P., et al.: TASK: Sensor Network in a Box. In: EWSN (2005)
Chandrasekaran, S., et al.: TelegraphCQ: Continuous Dataflow Processing for an Uncertain World. In: CIDR (2003)
Cooper, O., et al.: HiFi: A Unified Architecture for High Fan-in Systems. In: VLDB (2004)
Demand-response, http://dr.me.berkeley.edu/
Deshpande, A., et al.: Model-Driven Data Acquisition in Sensor Networks. In: VLDB Conference (2004)
Dey, A.K.: Providing Architectural Support for Building Context-Aware Applications. Ph.D. thesis, Georgia Institute of Technology (2000)
Elnahrawy, E., et al.: Cleaning and querying noisy sensors. In: WSNA 2003: Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications (2003)
Fishkin, K.P., Jiang, B., Philipose, M., Roy, S.: I Sense a Disturbance in the Force: Unobtrusive Detection of Interactions with RFID-tagged Objects. In: Davies, N., Mynatt, E.D., Siio, I. (eds.) UbiComp 2004. LNCS, vol. 3205, pp. 268–282. Springer, Heidelberg (2004)
Floerkemeier, C., Lampe, M.: Issues with RFID usage in ubiquitous computing applications. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 188–193. Springer, Heidelberg (2004)
Franklin, M.J., et al.: Design Considerations for High Fan-In Systems: The HiFi Approach. In: CIDR (2005)
Galhardas, H., et al.: Declarative data cleaning: Language, model, and algorithms. In: VLDB, pp. 371–380 (2001)
Gay, D., et al.: The nesC language: A holistic approach to networked embedded systems. In: SIGPLAN (2003)
Informatica, http://www.informatica.com/
Intel Lab Data, http://berkeley.intel-research.net/labdata/
Jeffery, S.R., et al.: A Pipelined Framework for Online Cleaning of Sensor Data Streams. In: ICDE (2006)
Kidd, C.D., et al.: The Aware Home: A Living Laboratory for Ubiquitous Computing Research. In: Cooperative Buildings, pp. 191–198 (1999)
Madden, S., et al.: The Design of an Acquisitional Query Processor For Sensor Networks. In: SIGMOD (2003)
Mukhopadhyay, S., et al.: Data aware, low cost error correction for wireless sensor networks. In: WCNC (2004)
Paskin, M.A., et al.: A robust architecture for distributed inference in sensor networks. In: IPSN (2005)
Philipose, M., et al.: Mapping and Localization with RFID Technology. Technical Report IRS-TR-03-014, Intel Research (December 2003)
Qin, S.: Neural networks for intelligent sensors and control — practical issues and some solutions. In: Neural Networks for Control (1996)
Rahm, E., et al.: Data cleaning: Problems and current approaches. IEEE Data Eng. Bull. 23(4), 3–13 (2000)
Särndal, C.-E., et al.: Model Assisted Survey Sampling. Springer Series in Statistics. Springer, New York (1992)
Sonoma Redwood Sensor Network Deployment, http://www.cs.berkeley.edu/~get/sonoma/
Tolle, G., et al.: A macrosope in the redwoods. In: SenSys (2005)
X10, http://www.x10.com
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Jeffery, S.R., Alonso, G., Franklin, M.J., Hong, W., Widom, J. (2006). Declarative Support for Sensor Data Cleaning. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds) Pervasive Computing. Pervasive 2006. Lecture Notes in Computer Science, vol 3968. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11748625_6
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DOI: https://doi.org/10.1007/11748625_6
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