The Internet ofThings(IoT)is a new model that evolved with the rapid progress of advanced technology and gained tremendous popularity due to its applications.Anomaly detection haswidely attracted researchers’attentio...The Internet ofThings(IoT)is a new model that evolved with the rapid progress of advanced technology and gained tremendous popularity due to its applications.Anomaly detection haswidely attracted researchers’attention in the last few years,and its effects on diverse applications.This review article covers the various methods and tools developed to perform the task efficiently and automatically in a smart city.In this work,we present a comprehensive literature review(2011 onwards)of three major types of anomalies:network anomalies,sensor anomalies,and videobased anomalies,along with their methods and software tools.Furthermore,anomaly detection methods such as machine learning and deep learning are presented in this work,highlighting their detection strategy techniques,features,applications,issues,and challenges.Moreover,a generic algorithmis also developed to ease the user achieve the taskmore specifically by targeting a specific domain aswell as approach.Comparative studies of three anomalymethods and their analysis identify research discovery areas with their applications.As a result,researchers and practitioners can familiarize themselves with the existing methods for solving real problems,improving methods,and developing new optimum methods for anomaly detection in diverse applications.展开更多
文摘The Internet ofThings(IoT)is a new model that evolved with the rapid progress of advanced technology and gained tremendous popularity due to its applications.Anomaly detection haswidely attracted researchers’attention in the last few years,and its effects on diverse applications.This review article covers the various methods and tools developed to perform the task efficiently and automatically in a smart city.In this work,we present a comprehensive literature review(2011 onwards)of three major types of anomalies:network anomalies,sensor anomalies,and videobased anomalies,along with their methods and software tools.Furthermore,anomaly detection methods such as machine learning and deep learning are presented in this work,highlighting their detection strategy techniques,features,applications,issues,and challenges.Moreover,a generic algorithmis also developed to ease the user achieve the taskmore specifically by targeting a specific domain aswell as approach.Comparative studies of three anomalymethods and their analysis identify research discovery areas with their applications.As a result,researchers and practitioners can familiarize themselves with the existing methods for solving real problems,improving methods,and developing new optimum methods for anomaly detection in diverse applications.
