Application of Predictive Analytics in IOT Data Processing

Abstract

Working with predictive models mean huge
opportunities for the business-using real-time data, while the
rapid growth of the Internet of Things-(IoT)-provides unique
opportunities and hurdles to business. Predictive analytics has
emerged as a cutting-edge approach in the analysis of vast and
intricate IoT datasets, using statistics, machine learning
algorithms, and artificial intelligence. In other words, this
chapter elaborates on how predictive analytics could fit into IoT
data management as an enabler for proactive decision-making
and outlines its use in forecasting trends, behaviours, and
outcomes.
Use in manufacturing, transportation, health, and agriculture,
where predictive models reduce risk, improves efficiency, and
optimize operating processes spanning a wide array of potential
sectors in following. The chapter, too, addresses privacy,
scalability, and quality of data concerns and proposes various
developments, such as edge computing, Explainable AI, and
sustainable analytics, as areas for further development. Pretty
much, predictive analytics impinges heavily into creating
smarter and data-driven solutions and promoting innovation
across diverse sectors.