A Survey on the Impact of Intelligent Surfaces in the Terahertz Communication Channel Models.

Terahertz (THz) band will play an important role in enabling sixth generation (6G) envisioned applications. Compared with lower frequency signals, THz waves are severely attenuated by the atmosphere temperature, pressure, and humidity. Thus, designing a THz communication system must take into account how to circumvent or diminish those issues to achieve a sufficient quality of service. Different solutions are being analyzed: intelligent communication environments, ubiquitous artificial intelligence, extensive network automation, and dynamic spectrum access, among others. This survey focuses on the benefits of integrating intelligent surfaces (ISs) and THz communication systems by providing an overview of IS in wireless communications with the scanning of the recent developments, a description of the architecture, and an explanation of the operation. The survey also covers THz channel models, differentiating them based on deterministic and statistical channel modeling. The IS-aided THz channels are elucidated at the end of the survey. Finally, discussions and research directions are given to help enrich the IS field of research and guide the reader through open issues.

Smart Strawberry Farming Using Edge Computing and IoT.

Strawberries are sensitive fruits that are afflicted by various pests and diseases. Therefore, there is an intense use of agrochemicals and pesticides during production. Due to their sensitivity, temperatures or humidity at extreme levels can cause various damages to the plantation and to the quality of the fruit. To mitigate the problem, this study developed an edge technology capable of handling the collection, analysis, prediction, and detection of heterogeneous data in strawberry farming. The proposed IoT platform integrates various monitoring services into one common platform for digital farming. The system connects and manages Internet of Things (IoT) devices to analyze environmental and crop information. In addition, a computer vision model using Yolo v5 architecture searches for seven of the most common strawberry diseases in real time. This model supports efficient disease detection with 92% accuracy. Moreover, the system supports LoRa communication for transmitting data between the nodes at long distances. In addition, the IoT platform integrates machine learning capabilities for capturing outliers in collected data, ensuring reliable information for the user. All these technologies are unified to mitigate the disease problem and the environmental damage on the plantation. The proposed system is verified through implementation and tested on a strawberry farm, where the capabilities were analyzed and assessed.

Literature Review on Ship Localization, Classification, and Detection Methods Based on Optical Sensors and Neural Networks.

Object detection is a common application within the computer vision area. Its tasks include the classic challenges of object localization and classification. As a consequence, object detection is a challenging task. Furthermore, this technique is crucial for maritime applications since situational awareness can bring various benefits to surveillance systems. The literature presents various models to improve automatic target recognition and tracking capabilities that can be applied to and leverage maritime surveillance systems. Therefore, this paper reviews the available models focused on localization, classification, and detection. Moreover, it analyzes several works that apply the discussed models to the maritime surveillance scenario. Finally, it highlights the main opportunities and challenges, encouraging new research in this area.

Performance Analysis of the IEEE 802.15.4 Protocol for Smart Environments under Jamming Attacks.

Jamming attacks in wireless sensor networks (WSNs) scenarios are detrimental to the performance of these networks and affect the security and stability of the service perceived by users. Therefore, the evaluation of the effectiveness of smart environment platforms based on WSNs has to consider the system performance when data collection is executed under jamming attacks. In this work, we propose an experimental testbed to analyze the performance of a WSN using the IEEE 802.15.4 CSMA/CA unslotted mode under jamming attacks in terms of goodput, packet receive rate (PRR), and energy consumption to assess the risk for users and the network in the smart scenario. The experimental results show that constant and reactive jamming strategies severely impact the evaluated performance metrics and the variance' of the received signal strength (RSS) for some signal-to-interference-plus-noise ratio (SINR) ranges. The measurements obtained using the experimental testbed were correlated with analytical models. The results show that in the presence of one interferer, for SINR values higher than 4.5 dB, the PRR is almost 0.99, and the goodput 3.05 Kbps, but the system performance is significantly degraded when the amount of interferers increases. Additionally, the energy efficiency associated with reactive strategies is superior to the constant attack strategy. Finally, based on the evaluated metrics and with the proposed experimental testbed, our findings offer a better understanding of jamming attacks on the sensor devices in real smart scenarios.

Cooperative Full-Duplex V2V-VLC in Rectilinear and Curved Roadway Scenarios.

We study here the vehicle-to-vehicle (V2V) visible light communication (VLC) between two cars moving along different roadway scenarios: (i) a multiple-lane rectilinear roadway and (ii) a multiple-lane curvilinear roadway. Special emphasis was given to the implementation of full-duplex (FD) cooperative communication protocols to avoid communication disruption in the absence of a line-of-sight (LOS) channel. Importantly, we found that the cooperative FD V2V-VLC is promising for avoiding communication disruptions for cars traveling in realistic curvilinear roadways. Results in this work can be easily extended to the case of vehicle-to-infrastructure (V2I), which can also be promising in cases of low-car-density environments.