Multi-Criterion Decision Making for Planning in Internet of Things Environment

Abstract

Over the recent few years, there is massive demand of internet related technologies and Internet of
Things(IOT) has emerged as a very competent source to capture meaningful business information
through advanced sensors. There are a lot of applications that are relying on big data and internet of
things. Large volumes of data are being pumped from the business environments and are being
trusted for business monitoring and control goals for various kinds of big industrial plants, traffic
control, retail management or even small applications. The data streams generated and maintained
using big data are generally used for making long term decisions while IoT is used for making
dynamic decisions at faster response rate. In this paper, we have tried to present an approach to
sample and rank the critical business data from the incoming data sample streams and make
decisions on the monitoring and management of the business based upon the few high ranked samples
so that the decision making is more focused towards the optimum solution of the problem. We have
used Hasse average ranking and absolute ranking for ranking the sampled data set of traffic data of
city of Sao Paulo