IoT Revolutionized: How Machine Learning is Transforming Data, Applications, and Industries
IoT Revolutionized: How Machine Learning is Transforming Data, Applications, and Industries
Author(s): Taiwo Abdulahi Akintayo, Raphael Aduramimo Olusola, Ewemade Cornelius Enabulele, Ayodele Oyesanya, Samuel Ayanwunmi Olanrewaju, Moyosore Owoeye Celestina, Balogun Oluwaseyi Sulaimon, Ogechukwu Ada Lorretta Anoliefo, Ayanwunmi Victor Olumide, Olamilekan Jamiu Ridwan, Adedokun Seyi AdediranSubject(s): Methodology and research technology, ICT Information and Communications Technologies
Published by: Altezoro, s. r. o. & Dialog
Keywords: Internet of Things (IoT); Machine Learning (ML); Sensor Data; Intelligent Decision-Making; Data Analysis; Smart Environments; Internet of Behavior;
Summary/Abstract: Integrating machine learning (ML) with the Internet of Things (IoT) reveals hidden patterns and insights from extensive sensor data, enabling IoT to become omnipresent and make intelligent decisions without explicit programming. ML is essential for IoT to meet the future needs of businesses, governments, and individuals. IoT aims to sense its environment and automate decision-making through intelligent methods, emulating human decisions. This paper reviews and categorises existing literature on ML-enabled IoT from three perspectives: data, applications, and industries. We examine advanced methods and applications by reviewing various sources, emphasising how ML and IoT work together to create more innovative environments. We also discuss emerging trends such as the Internet of Behavior, pandemic management, autonomous vehicles, edge and fog computing, and lightweight deep learning. Furthermore, we identify challenges to IoT in four categories: technological, individual, business, and societal. This paper aims to leverage IoT opportunities and address challenges for a more prosperous and sustainable future.
Journal: Traektoriâ Nauki
- Issue Year: 10/2024
- Issue No: 6
- Page Range: 8001-8007
- Page Count: 7
- Language: English
