Outlier Detection Techniques for Wireless Sensor Networks: A Survey

By Yang Zhang, Nirvana Meratnia, Paul J. M. Havinga. IEEE Communications Surveys and Tutorials, 2008

843 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Outlier Detection for Temporal Data: A Survey (2014, background): “[4] provide an extensive overview of out-lier detection techniques.”
An Adaptive Bayesian System for Context-Aware Data Fusion in Smart Environments (2017, background): “The problem of detecting sensory measurements that mismatch with the expected pattern of observed data has been thoroughly studied in the literature [11], with the aim of eliminating outliers from the fusion process.”
Anomaly detection in online social networks (2014, methodology): “In addition, anomaly detection in sensor networks generally requires algorithms that reduce network traﬃc and have a low computational complexity (Zhang et al., 2010).”
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications (2014, background): “The major challenge to implement security techniques in WSNs is the limited resource constraints [14].”
Anomaly Detection for IoT Time-Series Data: A Survey (2020, background): “Where the sensors are powered by battery these challenges are often ampliﬁed as the available charge decreases [37], it is often possible to aggregate data from multiple similar sensors into a single observation to reduce the environmental noise.”