Artificial intelligence empowered NB-IoT systems: architectures, advances, and future perspectives
Abstract
Abstract With an increasing number of devices being installed in agriculture, factories, hospitals, and cities, the need for intelligent, trustworthy, and energy-efficient communication systems is rising. This is one such system: Narrow Band Internet of Things, or NB-IoT, which connects devices at a long range with low-power consumption. But it also has a poor reaction time and is not adaptable to changing situations. This review discusses how artificial intelligence (AI), including machine learning (ML), deep learning, and other intelligent methods, are making NB-IoT more adaptable and predictive. By deploying lightweight AI models and edge computing—that is, processing locally on a device—systems are able to better manage wireless signals, save battery life, and improve overall performance. It also discusses several related real-world applications in the area of agriculture, healthcare, industry, and smart cities and achieves benefits such as saving water, early disease diagnosis, predictive machine maintenance, and environmental monitoring. The integration of AI with NB-IoT fosters digital solutions toward sustainability, security, and being human-centric. All the progress made thus far will be of immense utility to decision-makers, engineers, planners of smart cities, and service providers who look to smarter, more affordable, privacy-friendly technology for the future.
