Wireless sensor networks had been deployed in the real world to collect large amounts of raw sensed data. However, the key challenge is to extract high level knowledge from such raw data. Sensor networks applications, outlier/anomaly detection has been paid more and more attention. The propose of a classification approach that provides outlier detection and data classification simultaneously. Experiments on Intel Berkley lab sensor dataset show that the proposed approach outperforms other techniques in both effectiveness & efficiency. Keywords:Outlier Detection,Data mining,Wireless sensor Network,Decision tree
A wireless sensor network (WSN) is defined as a set of spatially distributed and interconnected sens...
A wireless sensor network (WSN) is defined as a set of spatially distributed and interconnected sens...
Wireless sensor networks (WSNs) have recently attracted greater attention worldwide due to their pra...
In the field of wireless sensor networks, measurements that significantly deviate from the normal pa...
In the field of wireless sensor networks, those measurements that significantly deviate from the nor...
In the past few years, many wireless sensor networks had been deployed in the real world to collect ...
Abstract—In the field of wireless sensor networks, those measurements that significantly deviate fro...
AbstractIn the past few years, many wireless sensor networks had been deployed in the real world to ...
Raw data collected in wireless sensor networks are often unreliable and inaccurate due to noise, fau...
International audienceOutliers in wireless sensor networks are measurements that deviate from the no...
Detecting outliers has been a well studied problem in many applicable fields of research. Yet, wirel...
The generation of wireless sensor networks (WSNs) makes human beings observe and reason about the ph...
Data sets collected from wireless sensor networks (WSN) are usually considered unreliable and subjec...
is a demandable, efficient and emerging area of Computer Science Engineering which has been currentl...
Data anomaly detection in wireless sensor networks, which is one of the important technologies and s...
A wireless sensor network (WSN) is defined as a set of spatially distributed and interconnected sens...
A wireless sensor network (WSN) is defined as a set of spatially distributed and interconnected sens...
Wireless sensor networks (WSNs) have recently attracted greater attention worldwide due to their pra...
In the field of wireless sensor networks, measurements that significantly deviate from the normal pa...
In the field of wireless sensor networks, those measurements that significantly deviate from the nor...
In the past few years, many wireless sensor networks had been deployed in the real world to collect ...
Abstract—In the field of wireless sensor networks, those measurements that significantly deviate fro...
AbstractIn the past few years, many wireless sensor networks had been deployed in the real world to ...
Raw data collected in wireless sensor networks are often unreliable and inaccurate due to noise, fau...
International audienceOutliers in wireless sensor networks are measurements that deviate from the no...
Detecting outliers has been a well studied problem in many applicable fields of research. Yet, wirel...
The generation of wireless sensor networks (WSNs) makes human beings observe and reason about the ph...
Data sets collected from wireless sensor networks (WSN) are usually considered unreliable and subjec...
is a demandable, efficient and emerging area of Computer Science Engineering which has been currentl...
Data anomaly detection in wireless sensor networks, which is one of the important technologies and s...
A wireless sensor network (WSN) is defined as a set of spatially distributed and interconnected sens...
A wireless sensor network (WSN) is defined as a set of spatially distributed and interconnected sens...
Wireless sensor networks (WSNs) have recently attracted greater attention worldwide due to their pra...