For classification data, we use Wireless sensor networks (WSNs) as hardware for collecting data from harsh environments and controlling important events in ...

Abstract—For classification data, we use Wireless sensor networks (WSNs) as hardware for collecting data from harsh environments and controlling important ...

In this paper we propose a novel in-network knowledge discovery approach that provides outlier detection and data clustering simultaneously.

Outlier detection can be used to filter noisy data, find faulty nodes, and discover interesting events. In this paper we propose a novel in-network knowledge ...

Outlier detection aims at identify- ing anomalous readings by comparing sensor measurements with each other, while event detection aims at specifying a certain ...

2018/02/05 · Samples are tagged as outliers if they do not belong to a cluster of normal data or if their clusters are substantially smaller than the normal ...

The identification of outliers in WSNs can be used for filtration of false data, find faulty nodes and discover events of interest. This paper presents a survey ...

2024/03/14 · Li, “Outlier detection in wireless sensor networks using model selection-based support vector data descriptions,” Sensors, vol. 18, no. 12 ...

2013/07/10 · tralized outlier detection, both the clustering algorithm and outlier detection algorithm are performed after all data from each sensor node ...

For classification data, we use Wireless sensor networks (WSNs) as hardware for collecting data from harsh environments and controlling important events in ...