• DOI:10.1109/SMC.2013.9
Corpus ID: 6434158

Anomaly Detection in Sensor Systems Using Lightweight Machine Learning

@article{Bosman2013AnomalyDI,
  title={Anomaly Detection in Sensor Systems Using Lightweight Machine Learning},
  author={H. J. Bosman and A. Liotta and Giovanni Iacca and H. W{\"o}rtche},
  journal={2013 IEEE International Conference on Systems, Man, and Cybernetics},
  year={2013},
  pages={7-13}
}

• H. J. Bosman, A. Liotta, +1 author H. Wörtche
• Published 2013
• Computer Science
• 2013 IEEE International Conference on Systems, Man, and Cybernetics

The maturing field of Wireless Sensor Networks (WSN) results in long-lived deployments that produce large amounts of sensor data. Lightweight online on-mote processing may improve the usage of their limited resources, such as energy, by transmitting only unexpected sensor data (anomalies). We detect anomalies by analyzing sensor reading predictions from a linear model. We use Recursive Least Squares (RLS) to estimate the model parameters, because for large datasets the standard Linear Least… Expand

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