Machine Learning-Enabled Internet of Things (IoT): Data, Applications, and Industry Perspective

Abstract

Machine learning (ML) allows the Internet of Things (IoT) to gain hidden insights from the treasure trove of sensed data and be truly ubiquitous without explicitly looking for knowledge and data patterns. Without ML, IoT cannot withstand the future requirements of businesses, governments, and individual users. The primary goal of IoT is to perceive what is happening in our surroundings and allow automation of decision-making through intelligent methods, which will mimic the decisions made by humans. In this paper, we classify and discuss the literature on ML-enabled IoT from three perspectives: data, application, and industry. We elaborate with dozens of cutting-edge methods and applications through a review of around 300 published sources on how ML and IoT work together to play a crucial role in making our environments smarter. We also discuss emerging IoT trends, including the Internet of Behavior (IoB), pandemic management, connected autonomous vehicles, edge and fog computing, and lightweight deep learning. Further, we classify challenges to IoT in four classes: technological, individual, business, and society. This paper will help exploit IoT opportunities and challenges to make our societies more prosperous and sustainable.

Investigation of Impact of Temperature on Proposed Device with Reference to DIEL CYCLE

“…Sugar cane is another crucial cash crop that Nilgai uses as a great cover (Blue Bull or Antelope). Because when crops like corn is fully grown, rat eats and destroys plants and cereals like maize [8] [3].…”

A Step toward Next-Generation Advancements in the Internet of Things Technologies

“…The output useful applications are data analysis and business models. ML modules are helpful to find the hidden insights of sensed data in the IoT [ 68 ]. In addition, it is also used to predict the future requirements of individual users, governments, businesses, as shown in Figure 10 .…”

“…In addition, it is also used to predict the future requirements of individual users, governments, businesses, as shown in Figure 10 . The goal of the IoT is to perceive what is happing in our surrounding environment and allow the automation of decision-making using intelligent methods [ 68 ]. The IoT aims to understand what people want and how people think, predict unwanted events, and learn and manage certain situations.…”

“…The IoT needs to understand the data which have been processed by millions of objects. To do this, ML algorithms play an important role in the IoT [ 68 ]. The IoT technology is ubiquitous by nature, which means that it is available everywhere.…”

“…The IoT technology is ubiquitous by nature, which means that it is available everywhere. ML plays an important role in digging out the data produced by the millions of connected devices [ 68 ]. The trends and tendencies of ML are used to find the patterns and may be the underpinning for human-like intelligence.…”