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Sixth-generation (6G) wireless communications and networks will continue to move to higher frequency and wider bandwidth, with much higher data rate and spectral efficiency. Given the heterogeneity and densification of Internet of Things (IoT), 6G wireless network may need to be extended to modern random access (RA) for IoT applications, which can be achieved via smart protocol design and advanced

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A typical Internet-of-Things (IoT) system consists of three major layers: 1) sensing; 2) communication; and 3) application (i.e., actuation and control) layers. The co-design of these layers has been studied for over two decades, dating back to the concept of communication, computing, and control, i.e., 3C, convergence in the 1990s. Nowadays, with the emergence of wireless-networked machine-type applications

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Recently, the Internet of Things (IoT) technologies have made their entrances into many fields, such as smart city, healthcare, intelligent transportation, forest protection, and environmental monitoring.

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As authors of our recently accepted article: Aggregate Cyber-Risk Management in the IoT Age: Cautionary Statistics for (Re)Insurers and Likes , published in the IEEE IoT Journal, we regret that we have found a few errors in the numerical evaluation setup of the works in [1] and [2] that we had borrowed for our accepted paper. In this correction statement, we describe the errors in detail, correct it

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The Internet of Things (IoT) enables the interconnection of new cyber–physical devices that generate significant traffic of distributed, heterogeneous, and dynamic data at the network edge. Since several IoT applications demand for short response times (e.g., industrial applications, emergency management, real-time systems, and healthcare systems) and, at the same time, rely on resource-constrained

This article proposes a novel ultralarge-scale crowd monitoring system, namely, the ULCM system. The ULCM system enables advanced sensing and networking technologies aimed at collecting and processing multimodal, multiperspective, and real-time crowding data relevant to crowd management. This data will be further analyzed to provide a global realization of evolving events over a large geographical

Efficient video processing is a critical component in many IoMT applications to detect events of interest. Presently, many window optimization techniques have been proposed in event processing with an underlying assumption that the incoming stream has a structured data model. Videos are highly complex due to the lack of any underlying structured data model. Video stream sources, such as CCTV cameras

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The Internet of Things (IoT) has created a ubiquitously connected world powered by a multitude of wired and wireless sensors generating a variety of heterogeneous data over time in a myriad of fields and applications. To extract complete information from these data, advanced artificial intelligence (AI) technology, especially deep learning (DL), has proved successful in facilitating data analytics

This article provides a survey about the state of the art in embedded intelligence (EI) research for smart cities. Currently, a comprehensive survey for EI research for smart cities is not available. This article presents a comprehensive review and discusses representative studies of the emerging and current paradigms for EI with the focus on the enabling technologies, applications, and challenges

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Today, the Internet of Things (IoT) is increasingly flourishing with establishing ubiquitous connections between smart devices and objects, and by 2020, there will be a total of 30 billion connected things reported by IDC. The unprecedented data explosion provides immense opportunities for valuable information mining. At the same time, it also floods the infrastructure with tremendous values it necessarily

The Emerging unmanned aerial vehicles (UAVs) have been widely exploited for sensing purposes due to the larger service coverage compared with the conventional fixed sensor nodes. However, due to the limited computation capability of UAVs, real-time sensory data needs to be transmitted to the BS/server for real-time data processing. In this regard, the cellular networks are necessary to support the

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The Internet of Things (IoT) has important applications in our daily lives, including health and fitness tracking, environmental monitoring, and transportation. However, sensor nodes in IoT suffer from the limited lifetime of batteries resulting from their finite energy availability. A promising solution is to harvest energy from environmental sources, such as solar, kinetic, thermal, and radio-frequency

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The atmospheric buoyancy and intangible nature of fatal communicable viruses lead to rapid transmissions among individuals, resulting in global pandemics. Strategic lockdowns and mandatory social distancing are immediate solutions in such scenarios. However, this leads to operational disruptions in education, manufacturing, economy, transportation, governance, and community. Although technological

Mobile-edge computing is a promising computing paradigm with the advantages of reduced delay and relieved outsourcing traffic to the core network. In mobile-edge computing, reducing the computation offloading cost of mobile users and maintaining fresh information at edge nodes are two critical while conflicted objectives, as both consume the limited wireless bandwidth of edge nodes. Although extensive

The sensor technology for water quality monitoring (WQM) has improved during recent years. The cost-effective sensorised tools that can autonomously measure the essential physical–chemical–biological (PCB) variables are now readily available and are being deployed on buoys, boats, and ships. Yet, there is a disconnect between the data quality, data gathering, and data analysis due to the lack of standardized