The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Advanced Machine Learning Innovations in Embedded Systems and Narrowband Internet of Things (NB-IoT) Devices
|
|
Author(s): M. Dhanalakshmi (Department of Computer Science and Engineering, New Horizon College of Engineering, Bangalore, India), G. Nand Kishor Kumar (Department of Computer Science and Engineering, Malla Reddy University, Hyderabad, India), Goli Himabindu (Department of Cyber Security, Geethanjali College of Engineering, Hyderabad, India), Vinodpuri Rampuri Gosavi (Department of Electronics and Telecommunication Engineering, Sandip Institute of Technology and Research Center, Nashik, India), C. S. Sundar Ganesh (Department of Electrical and Electronics Engineering, Karpagam College of Engineering, Coimbatore, India)and R. Premanand (Sri Sai Ram Engineering College, Chennai, India)
Copyright: 2025
Pages: 26
Source title:
Integrating Artificial Intelligence Into the Energy Sector
Source Author(s)/Editor(s): Abdelkader Mohamed Sghaier Derbali (Taibah University, Saudi Arabia)
DOI: 10.4018/979-8-3693-7112-1.ch016
Purchase
|
Abstract
This chapter explores the convergence of machine learning (ML) and embedded systems in the context of Narrowband Internet of Things (NB-IoT) devices. It highlights the latest innovations that enable real-time data processing, decision-making, and predictive analytics on resource-constrained devices. The chapter delves into key ML techniques such as federated learning, edge AI, and lightweight neural networks that are transforming the capabilities of embedded systems and NB-IoT. Additionally, it discusses the challenges of implementing ML models in low-power environments and the strategies to overcome these limitations, including model compression, hardware accelerators, and efficient algorithms. Through case studies and practical applications, the chapter demonstrates how these advancements are driving the deployment of intelligent IoT solutions across various industries, including smart cities, healthcare, and industrial automation, paving the way for more autonomous, efficient, and scalable IoT ecosystems.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|