Prescriptive Analytical Models for Dynamic IoT Data Streams: A Review

Abstract

The application of data analysis tools and procedures to perceive value from vast volume of data created by connected IoT devices is known as IoT data analytics. Many IoT applications are made up of disparate streams that must be merged and turned into complete, consistent, current, and accurate data for business reporting and analysis. While predictive analytics on IoT dealing with the prediction involved with the setting of IoT appliances, the next stage of IoT data analytics maturity involves deriving actionable insights from predictions made in previous stages. The earlier descriptive, diagnostic, and predictive IoT analytics blog segments took the process one step closer to optimal decision making, prescriptive analytics takes it the rest of the way. Prescriptive analytics is an emerging approach in the data analytics community that requires much attention to employ it in various fields of technology. It is a promising approach in IoT data analytics that focuses on discovering the distinguished action necessary for a particular circumstance, based on data. In this paper, an overview of IoT data analytics, survey of prescriptive analytical models, applications, issues, challenges and platforms for IoT analytics are discussed.