TY - JOUR
T1 - Machine Learning for Smart Environments in B5G Networks
T2 - Connectivity and QoS
AU - Alsamhi, Saeed H.
AU - Almalki, Faris A.
AU - Al-Dois, Hatem
AU - Ben Othman, Soufiene
AU - Hassan, Jahan
AU - Hawbani, Ammar
AU - Sahal, Radyah
AU - Lee, Brian
AU - Saleh, Hager
N1 - Publisher Copyright:
© 2021 Saeed H. Alsamhi et al.
PY - 2021
Y1 - 2021
N2 - The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and introduce vulnerabilities. Intelligent management of IoT is required to maintain connectivity, improve Quality of Service (QoS), and reduce energy consumption in real time within dynamic environments. Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications. We also provide an in-depth overview of the variety of IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare. For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works.
AB - The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and introduce vulnerabilities. Intelligent management of IoT is required to maintain connectivity, improve Quality of Service (QoS), and reduce energy consumption in real time within dynamic environments. Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications. We also provide an in-depth overview of the variety of IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare. For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works.
UR - http://www.scopus.com/inward/record.url?scp=85116643349&partnerID=8YFLogxK
U2 - 10.1155/2021/6805151
DO - 10.1155/2021/6805151
M3 - Review article
C2 - 34589123
AN - SCOPUS:85116643349
SN - 1687-5265
VL - 2021
JO - Computational Intelligence and Neuroscience
JF - Computational Intelligence and Neuroscience
M1 - 6805151
ER -
