Advance Algorithm for Anomaly Detection for Smart Home: A Comprehensive Approach

Abstract

Wireless Sensor Networks (WSN) are significant and essential platforms for the prospect since they have emerged along the concept of the "Internet of Things." They are utilized to oversee, monitor, and administer a diverse array of Applications in the realms of business, healthcare, the natural world, and the military. Nevertheless, the accuracy of data together through sensor nodes is impacted by anomalies that happen due to many factors, including node failures, reading mistakes, unusual procedures, and malicious attacks. Consequently, anomaly detection is a crucial procedure to verify the precision of sensor data before its use in decision-making. This study examines the challenges associated with anomaly detection in WSN and outlines the necessity for creating a highly efficient and successful anomaly detection model. In this segment, we will explore the latest developments in research on data anomalies detecting in Wireless Sensor Networks (WSN). We will categorize the existing detection strategies into five foremost groups based on the procedures used to build them. The text examines several advanced models for every category, highlighting their limits, along with providing recommendations for further research. In addition, the examined options are associated and evaluated based on their alignment along the specified criteria. Ultimately, the inherent limits of existing methods are recognized, and further avenues for exploration are suggested and taken into account.