Big Data Analytics Algorithm, Data Type and Tools in Smart City: A Systematic Literature Review

Abstract

The smart city generated rapidly huge of data. Data can analyze with big data analytics technology to give solution from past data in smart city problem and help better solution in decision making. This paper summarizes the existing condition of big data analytics in the smart city in term of the algorithm, data type and tools were built using systematic literature review (SLR) as the standard methodology used to solve any problem by tracing the result from the previous research. The problem in SLR called as research question (RQ). To achieve that goal, we define some RQs related to that scope and clarify each question by tracing previous research. The research paper from reputable journal databases such as IEEE Xplore, Scopus, ScienceDirect, and Springerlink. After synthesizing 15 articles, the results are: algorithm data mining like ANN, Markov, graph mining, etc. needs to improve. That algorithm not enough to handle high data volume, high variety and high velocity to store and processes data; main data type have big chance to give the solution in the smart city is social media. That data has the potential to help in decision making in the smart city problem; Hadoop is the top tool to store and analyze data with high-performance, stable, reliable computing for the different type of data. Combination Hadoop with spark give less overhead to handle the high velocity and volume of data.