Today, we cannot deny the massive growth of data that the world is facing and will absolutely suffer from in the future, especially with the vision of creating smart cities through all its services and devices. In fact, this data has many characteristics that depend on its source and destination use, which made it an important base for achieving the smart internal and external communication between different parts of the city. However, before processing it, real world data suffers from different problems that will affect the next stage of its usage in knowledge extraction process. In this paper, we are studying data improvement methods related to preprocessing techniques for big data usage and two frameworks for identifying and removing noise. In addition, we focus on two types of smart cities services by providing an overview for their data quality problems and improvements.
Volume 12 | 04-Special Issue
Pages: 1198-1204
DOI: 10.5373/JARDCS/V12SP4/20201594