Intersection of Artificial Intelligence, Machine Learning, and Internet of Things – An Economic Overview

Abstract

Internet of Things (IoT) has become one of the mainstream advancements and a supreme domain of research for the technical as well as the scientific world, and financially appealing for the business world. It supports the interconnection of different gadgets and the connection of gadgets to people. IoT requires a distributed computing set up to deal with the rigorous data processing and training; and simultaneously, it requires artificial intelligence (AI) and machine learning (ML) to analyze the information stored on various cloud frameworks and make extremely quick and smart decisions w.r.t to data. Moreover, the continuous developments in these three areas of IT present a strong opportunity to collect real-time data about every activity of a business. Artificial Intelligence (AI) and Machine Learning are assuming a supportive part in applications and use cases offered by the Internet of Things, a shift evident in the behavior of enterprises trying to adopt this paradigm shift around the world. Small as well as large-scale organizations across the globe are leveraging these applications to develop the latest offers of services and products that will present a new set of business opportunities and direct new developments in the technical landscape. The following transformation will also present another opportunity for various industries to run their operations and connect with their users through the power of AI, ML, and IoT combined. Moreover, there is still huge scope for those who can convert raw information into valuable business insights, and the way ahead to do as such lies in viable data analytics. Organizations are presently looking further into the data streams to identify new and inventive approaches to elevate proficiency and effectiveness in the technical as well as business landscape. Organizations are taking on bigger, more exhaustive research approaches with the assistance of continuous progress being made in science and technology, especially in machine learning and artificial intelligence. If companies want to understand the valuable capacity of this innovation, they are required to integrate their IoT frameworks with persuasive AI and ML algorithms that allow ’smart devices/gadgets’ to imitate behavioral patterns of humans and be able to take wise decisions just like humans without much of an intervention. Integrating both artificial intelligence and machine learning with IoT networks is proving to be a challenging task for the accomplishment of the present IoT-based digital ecosystems. Hence, organizations should direct the necessary course of action to identify how they will drive value from intersecting AI, ML, and IoT to maintain a satisfactory position in the business in years to come. In this review, we will also discuss the progress of IoT so far and what role AI and ML can play in accomplishing new heights for businesses in the future. Later the paper will discuss the opportunities and challenges faced during the implementation of this hybrid model.