Since the data gathered in Wireless Sensor Network (WSN) are inaccurate and unreliable, a flexible space model based on the spatial correlation of sensor data was defined, and an adaptive neighbor-space approach for data cleansing (ANSA) was proposed. The approach adjusted neighbor-space dynamically according to sensor data fluctuation and calculated the weighted average of neighbors' measurements to clean local raw data. The experimental results show that, the sensor data error after cleansing by the proposed approach is less than 0.5, and compared to the classic Weighted Moving Average (WMA), it is more accurate and the energy consumption is reduced by about 36%.
MARTINCIC F, SCHWIEBERT L. Distributed event detection in sensor networks ［C］// ICSNC'06: Proceedings of the 2006 IEEE International Conference on Systems and Networks Communications. Piscataway: IEEE Press, 2006: 43.
［2］
AKYILDIZ I F, VURAN M C, AKAN O B. On exploiting spatial and temporal correlation in wireless sensor networks ［C］// WiOpt'04: Proceedings of the 2004 Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks. Cambridge: University of Cambridge, 2004: 71-80.
［3］
JEFFERY S R, ALONSO G, FRANKLIN M J, et al. Declarative support for sensor data cleaning ［C］// Proceedings of the 4th International Conference on Pervasive Computing. Berlin: Springer, 2006: 83-100.
［4］
SHENG B, LI Q, MAO W, et al. Outlier detection in sensor networks ［C］// Proceedings of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing. New York: ACM Press, 2007: 219-228.
［5］
ZHUANG Y, CHEN L, WANG X S, et al. A weighted moving average-based approach for cleaning sensor data ［C］// ICDCS'07: Proceedings of the 27th IEEE International Conference on Distributed Computing Systems. Piscataway: IEEE Press, 2007: 38-38.
［6］
GUO L, FU H, ZHANG Z. Adaptive method for cleaning sensory data in wireless sensor networks [J]. Computer Engineering and Applications, 2009, 45(13): 150-155.(郭龙江,付惠娟,张中兆.传感器网络感知数据自适应去噪方法［J］.计算机工程与应用,2009,45(13):150-155.)
［7］
BRANCH J W, GIANNELLA C, SZYMANSKI B, et al. In-network outlier detection in wireless sensor networks ［J］. Knowledge and Information Systems, 2013, 34(1): 23-54.
［8］
ZHANG Y, MERATNIA N, HAVINGA P. Outlier detection techniques for wireless sensor networks: a survey ［J］. IEEE Communications Surveys and Tutorials, 2010, 12(2): 159-170.
［9］
FRANKE C, GERTZ M. ORDEN: outlier region detection and exploration in sensor networks ［C］// Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data. New York: ACM Press, 2009: 1075-1078.
［10］
JEFFERY S R, GAROFALAKIS M, FRANKLIN M J. Adaptive cleaning for RFID data streams ［C］// Proceedings of the 32nd International Conference on Very Large Data Bases. New York: ACM Press, 2006: 163-174.
［11］
ZHANG Z, YANG D, ZHANG T, et al. A study on the method for cleaning and repairing the probe vehicle data ［J］. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(1): 419-427.
［12］
FANG L, DOBSON S. In-network sensor data modelling methods for fault detection ［C］// AmI-2013: Proceedings of the Fourth International Joint Conference on Ambient Intelligence. Berlin: Springer, 2013: 176-189.
2014, Vol. 34 
