Data driven decision making for sustainable smart environments

Abstract

An exponential growth in the availability of data from various sources has enabled large scale adoption of data driven decision making. Much of present day's data was generated in the recent years, complementing to this there has been a substantial reduction in data storage costs. Hence the analysis of data collected will assist decision making in our future smart environments. Here sustainability refers to the large scale, robust data infrastructures for future organizations and cities that provide the basis for insightful actions w.r.t defined goals. New age databases can handle both structured and unstructured data with ease. Pooling this with statistical analytical tools promises to be a perfect recipe to cater the needs of decision making and to promote sustained self-sufficiency in smart environments. Actionable knowledge thus obtained can lead to improved understanding of human interaction with the systems driving smart environments. Our research analyses some of the technologies with which we can obtain meaningful actionable insights using the data captured from various underlying systems in a smart environment. A combination of SAP HANA, Hadoop, and R were deployed in our test bed. It's observed, how Smart devices coupled with smart big data analytics enables insightful actions and is the need of the hour to help us reduce operational redundancy and promote automation in the envisioned smart environments.