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Internet of Things (IoT) refers to an ecosystem where applications and services are driven by data collected from devices interacting with each other and the physical world. Although IoT has already brought spectacular benefits to human society, the progress is actually not as fast as expected. From network structures to control flow graphs, IoT naturally generates an unprecedented volume of graph

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Blockchain, as a constantly evolving Peer-to-Peer (P2P) distributed ledger technology with characteristics, such as decentralization, security, interoperation, and trust establishment, can potentially lower the costs of the underpinning infrastructure and maintenance compared with conventional centralized systems. Consequently, the distributed structure of blockchain is naturally suitable for the Internet

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An Analysis of many IoT deployments showed that most of them can address the sustainable development goals (SDGs) and the UN’s 2030 agenda. Interestingly, most of these projects concentrate on five SDGs: 1) industry, innovation, infrastructure; 2) smart cities and communities; 3) affordable and clean energy; 4) good health and well-being; and 5) responsible production and consumption. Examples include

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Mobile edge computing (MEC) is envisioned as a promising technique to support computation-intensive and time-critical applications in future Internet of Things (IoT) era. However, the uplink transmission performance will be highly impacted by the hostile wireless channel, the low bandwidth, and the low transmission power of IoT devices. Recently, intelligent reflecting surface (IRS) has drawn much

Satellite and unmanned aerial vehicle (UAV) integrated networks (SUINs) are considered as a promising method to offer various Internet of Remote Things (IoRT) applications. In this article, we investigate the downlink transmission of SUINs where the satellite-to-UAV link uses the free-space optical (FSO) technology with an equal gain combining (EGC) scheme while the links from UAV to IoRT devices exploit

Node failures are known to be among the generic problems in Internet of Things (IoT) networks. These failures can be caused by communication disturbances, battery depletion, or even hardware faults. The larger the IoT network and the larger the task to be executed in the network, the higher is the probability of a node failure in the relevant part of the network. This article studies the node failures

Advances in artificial intelligence (AI) and wireless technology are driving forward the large deployment of interconnected smart technologies that constitute cyber–physical systems (CPSs) and Internet of Things (IoT) for many commercial and military applications. CPS is characterized by communication, computing, and control engineering based on a large volume of data originating from various devices

Angle-of-Arrival (AoA) estimation is an important problem in passive radio-frequency identification (RFID) systems. Affixing an RFID tag array to an object enables to acquire its orientation information. However, the electromagnetic interaction between the tags can induce mutual coupling interference, distorting the RFID fingerprint measurements used for AoA estimation. Moreover, RFID reader modes

Technology is gradually being incorporated as an integral part of education. This technology includes the now pervasive presence of the Internet, but also the inclusion of devices that are worn by teachers and learners. Wearable devices have greatly facilitated data acquisition of educational subjects. This article provides an overview of what and how wearable devices have been used in education and

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Internet of Vehicles (IoV) is one of the most promising applications of Internet of Things (IoT) in the automotive industry, which can empower moving vehicles to exchange information with neighboring cars, roadside infrastructure, remote servers, traffic control centers, and so on. IoV expects to support a wide range of vehicular services, such as road safety, path planning, infotainment, and smart

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As The trajectory of the Internet of Things (IoT) is moving at a rapid pace, most companies and organizations are awash and drowning in massive amounts of data. Determining how to profit from data deluge and unlock its value can give companies an edge in the market because data have the potential to add tremendous value to many aspects of a business [A1]. The market has already seen a level of monetization

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Programmable logic controllers (PLCs), i.e., the core of control systems, are well-known to be vulnerable to a variety of cyber attacks. To mitigate this issue, we design PLC-Sleuth, a novel noninvasive intrusion detection/localization system for PLCs, which is built on a set of control invariants—i.e., the correlations between sensor readings and the concomitantly triggered PLC commands—that exist

Since Internet of Things (IoT) communications can enjoy many advantages brought by content-centric networking (CCN) in nature, there is an increasing interest on their integration for better information retrieval and distribution. Nevertheless, different from the conventional multimedia traffic of which contents are hardly changed, IoT data are always transient and updated by their producers according

Emerging Internet of Things (IoT) applications, such as cashier-less shopping, mobile ads targeting, and geo-based augmented reality (AR), are expected to bring us much more convenience and infotainment. To realize this amazing future, we need to feed these applications with user locations of (sub)meter-level resolution anytime and anywhere. Unfortunately, many widely used location sources are either

Reinforcement learning (RL) is increasingly being used to optimize resource-constrained wireless Internet of Things (IoT) devices. However, existing RL algorithms that are lightweight enough to be implemented on these devices, such as $Q$ -learning, converge too slowly to effectively adapt to the experienced information source and channel dynamics, while deep RL algorithms are too complex to be implemented

Due to the inherent openness of wireless channels and the restriction of communication resources and energy supply, the privacy protection of the sensing data transmission in the security-critical Internet of Medical Things (IoMT) has become a great challenge. In order to guarantee the privacy of IoMT sensing and transmission in a wireless wiretap channel and reduce the power consumption, a privacy-aware

Industrial Internet of Things (IIoT) systems connect a plethora of smart devices, such as sensors, actuators, and controllers, to enable efficient industrial productions in manners observable and controllable by human beings. Plain model-based and data-driven diagnosis approaches can be used for fault detection and isolation of specific IIoT components. However, the physical models, signal patterns

With accelerated advances in various technologies, drones, better known as unmanned aerial vehicles (UAVs), are increasingly commonplace and consequently have a more pronounced impact on society. For example, Internet of Drones (IoD), a new communication paradigm offering fundamental navigation assistance and access to information, has widespread applications ranging from agricultural drones in farming

Owing to provision of a long-range and robust link, LoRa technology has drawn attention for the use in industrial data collection networks. This article proposes a real-time LoRa protocol that can effectively deal with both periodic and aperiodic data. The slots in a frame are logically partitioned such that they are first scheduled for periodic data by a slot scheduling algorithm, and then, the remaining

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When a UAV broadcasts its location periodically during flight, a target will observe the strongest signal when the UAV is at the closest location; thus, the target can infer its location based on the observed signals and the UAV’s trajectory. We consider how to design trajectories for UAVs such that all targets can locate themselves, and the maximum length of trajectories is minimized. To make the

Over the last decade, machine learning (ML) and deep learning (DL) algorithms have significantly evolved and been employed in diverse applications, such as computer vision, natural language processing, automated speech recognition, etc. Real-time safety-critical embedded and Internet of Things (IoT) systems, such as autonomous driving systems, UAVs, drones, security robots, etc., heavily rely on ML/DL-based

In existing computing systems, such as edge computing and cloud computing, several emerging applications and practical scenarios are mostly unavailable or only partially implemented. To overcome the limitations that restrict such applications, the development of a comprehensive computing paradigm has garnered attention in both academia and industry. However, a gap exists in the literature, owing to

The paradigm of Internet of Vehicles (IoV) as an extension to the Internet of Things (IoT) concept can assist the development of smart cities. IoV relies on vehicular communications to allow vehicles to communicate in real time with other vehicles, roadside infrastructure, and pedestrians. The main goal is to enable not only road safety services but also time-constrained IoT applications. In this context

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