A Comprehensive Review on Artificial Intelligence/Machine Learning Algorithms for Empowering the Future IoT Toward 6G Era

Abstract

The evolution of the wireless network systems over decades has been providing new services to the users with the help of innovative network and device technologies. In recent times, the 5G network systems are about to be deployed which creates the opportunity to realize massive connectivity with high throughput, low latency, high energy efficiency and security. It also focuses on providing massive Internet of Things (IoT) network connectivity as well as services for good health, large-scale agricultural and industrial production, intelligent traffic control and electricity generation, transmission and distribution systems. However, the ever-increasing number of user devices is directing the researchers towards beyond 5G systems to allocate these user devices with higher bandwidth. Researches on the 6G wireless network systems have already begun to provide higher bandwidth availability for densely connected larger network devices with QoS surety. Researchers are leveraging artificial intelligence (AI)/machine learning (ML) for enhancing future IoT network operations and services. This paper attempts to discuss AI/ML algorithms that can help in developing energy efficient, secured and effective IoT network operations and services. In particular, our article concentrates on the major issues and factors that influence the design of the communication systems for future IoT with the integration of AI/ML. It also highlights application domains, including smart healthcare, smart agriculture, smart transportation, smart grid and smart industry that can operate efficiently and securely. Finally, this paper ends with the discussion on future research scopes with these algorithms in addressing the open issues of the future IoT network systems.

Healthcare Monitoring Using Low-Cost Sensors to Supplement and Replace Human Sensation: Does It Have Potential to Increase Independent Living and Prevent Disease?

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Machine Learning Assists IoT Localization: A Review of Current Challenges and Future Trends

“…Mahmood et al presented a review of machine learning algorithm applications for future IoT toward the 6G era [ 24 ]. The survey focused on the evaluation of communication networks (3G to 6G) and categorized the studies covered based on the algorithm type, which included heuristic, supervised, unsupervised, deep learning, reinforcement learning, deep reinforcement learning, and federated learning.…”

Securing 6G-enabled IoT/IoV networks by machine learning and data fusion

“…IoT and IoV are shaping the next generation of networking and communication [3]. IoT/IoV can be defined in different ways [49] and usually covers objects such as physical devices including sensors and vehicles [24]. Also, the meaning has expanded from local region to global region, covering different types of network such as local area network (LAN) and next-generation 6G mobile network.…”

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