A Framework for Multi-Sensor Data fusion in the Context of IoT Smart City Parking Data

Abstract

Now a day, things are communicating using the Internet, In the context of a smart city all things are interconnected and they are transferring the data to each other. Smart city subapplications like parking, pollution, traffic, transportation are some examples. By using the internet, we can combine with communication, the big challenge in a multi-sensory environment to fetch meaning full data from sensors. There are many of the methods are used to analyse and mine IoT data like classification, clustering, association rule, and regression, etc. The data is collected on the Internet of Things (IoT) from heterogeneous sources in different formats. Data Fusion is a method to operate on fused data that are collected from different sources. In the case of IoT, the concept of distributed data fusion work well. One of the popular IoT applications is Smart City, where we can collect data and analysis them according to need. In this research paper, the researcher introduced the new framework of data fusion where the data is collected from a different type of smart city sub-application. and framework deployment is done by parking data set of smart cities.