Outlier Detection in Sensor Data Using Machine Learning Techniques for IoT Framework and Wireless Sensor Networks: A Brief Study

摘要

Outlier or anomaly detection in the sensed data for Internet of Things framework and Wireless Sensor Networks is a growing trend among researchers. Wireless Sensor Networks form the basis for Internet of Things framework in which the sensors sense a huge amount of data based on which certain actions or decisions or taken. So, the quality of data must be thoroughly checked as any kind of outlier may degrade the quality of the data and hence affect the final decision. Thus, it becomes imperative to maintain the quality of the data. In this work, some machine learning approaches have been discussed which have proved their mettle in outlier detection.