A Comprehensive Survey on Imputation of Missing Data in Internet of Things

Abstract

The Internet of Things (IoT) is enabled by the latest developments in smart sensors, communication technologies, and Internet protocols with broad applications. Collecting data from IoT and generating information from these data become tedious tasks in real-life applications when missing data are encountered in datasets. It is of critical importance to deal with the missing data timely for intelligent decision-making. Hence, this survey attempts to provide a structured and comprehensive overview of the research on the imputation of incomplete data in IoT. The article starts by providing an overview of incomplete data based on the architecture of IoT. Then, it discusses the various strategies to handle the missing data, the assumptions used, the computing platform, and the issues related to them. The article also explores the application of imputation in the area of IoT. We encourage researchers and data analysts to use known imputation techniques and discuss various issues and challenges. Finally, potential future directions regarding the method are suggested. We believe this survey will provide a better understanding of the research of incomplete data and serve as a guide for future research.