In this paper, a fully transparent multiband antenna for vehicle communications is designed, fabricated, and analyzed. The antenna is coplanar waveguide-fed to facilitate its manufacture and increase its transmittance. An indium-tin-oxide film, a type of transparent conducting oxide, is selected as the conductive material for the radiation path and ground plane, with 8 ohms/square sheet resistance. The substrate is glass with a relative permittivity of 5.5, and the overall dimensions of the optimized design are 50 mm × 17 mm × 1.1 mm. The main antenna parameters, namely, sheet resistance, reflection coefficient, and radiation diagram, were measured and compared with simulations. The proposed antenna fulfills the frequency requirements for vehicular communications according to the IEEE 802.11p standard. Additionally, it covers the frequency bands from 1.82 to 2.5 GHz for possible LTE communications applied to vehicular networks.

In this paper, a dual-band graphene coplanar waveguide antenna is designed for smart cities and internet of things applications. A graphene film is chosen as the conductive material for the radiation patches and ground plane with a thickness of 240 μm and an electric conductivity of 3.5 × 10⁵ S/m. The dielectric is glass with a dielectric permittivity of 6 and a thickness of 2 mm. The implementation of the antenna on glass permits the integration of the antenna in smart cities and IoT applications. This antenna is based on two trapezoidal patches that generate the dual-band behavior. The overall dimensions of the antenna are 30 mm × 30 mm × 2 mm. The reflection coefficient, gain, and radiation patterns were measured and compared with the simulations. The antenna covers two frequency bands; the lower band covers the 2.45 GHz ISM band, and the upper band range covers from 4 to 7 GHz.

Water is a critical resource for human survival worldwide, and its availability and quality in natural reservoirs such as lakes and rivers must be monitored. In that way, wireless dynamic sensor networks can help monitor water quality. These networks have significantly advanced across various sectors, including industrial automation and environmental monitoring. Moreover, the Internet of Things has emerged as a global technological marvel, garnering interest for its ability to facilitate information visualization and ease of deployment—the combination of wireless dynamic sensor networks and the Internet of Things improves water monitoring and helps to care for this vital resource. This article presents the design and deployment of a wireless dynamic sensor network comprising a mobile node outfitted with multiple sensors for remote aquatic navigation and a stationary node similarly equipped and linked to a server via the IoT. Both nodes can measure parameters like pH, temperature, and total dissolved solids (TDS), enabling real-time data monitoring through a user interface and generating a database for future reference. The integrated control system within the developed interface enhances the mobile node’s ability to survey various points of interest. The developed project enabled real-time monitoring of the aforementioned parameters, with the recorded data being stored in a database for subsequent graphing and analysis using the IoT. The system facilitated data collection at various points of interest, allowing for a graphical representation of parameter evolution. This included consistent temperature trends, neutral and alkaline zone data for pH levels, and variations in total dissolved solids (TDS) recorded by the mobile node, reaching up to 100 ppm.

Latency is a determining factor in an IoT-enabled Intelligent Transportation System. To solve the latency issue in an edge computing system connected to the cloud, where the primary challenge is the distance between the end device and the cloud server, an implementation in a real urban environment is presented to illustrate the architecture of Intelligent Edge Computing. The IEC design is scalable through a communication system that incorporates latency and distance measurements in the transmission of a detection signal using deep learning at the edge node. This enabled the transmission of 2-byte detection signals to the fog node, where the received information was processed to count vehicles on up to three streets near the intersection. The vehicle detection signal is transmitted between two different embedded platforms. This architecture enabled an average transmission latency of 15.45 ms and a total end-to-end latency of 47.9087 ms over a distance of 600 m in a real-world urban environment. The IEC system leverages this low latency and offers intelligent processing closer to the data source and, therefore, to the user.

Wireless sensor networks (WSN) are increasingly present in applications of daily life, such as health care, agriculture, and environmental monitoring. According to the definition of a smart city, it requires connectivity to exchange information based on various technologies such as the WSN for the Internet of Things. Therefore, a 6LoWPAN is a type of hybrid network connected to the Internet through devices with limited resources using IPv6. For that reason, a 6LoWPAN becomes key in the implementation of a WSN. Due to the situation derived from COVID-19, the sanitary measures established indoor will allow the development of applications such as the one presented in this work, which establishes temperature monitoring in a university laboratory. The focus of this project is based on analyze of data transmission in a 6LoWPAN implemented through the IEEE 802.15.4 standard. The devices used correspond to the Texas Instruments CC2650stk and a CC2531 packet sniffer. The monitored data is stored in a database for graphical presentation.

This paper presents the design and implementation of a rectenna for energy harvesting at a frequency of 2.45 GHz. The stages that conform to the rectenna are described. We emphasized that the impedance match is essential to achieve adequate rectena performance. Regarding this, the input impedance of the rectifier was measured experimentally to design the match network. On the other hand, the antenna that makes up the rectenna is a microstrip patch antenna. The present rectenna was evaluated in three environments where the maximum voltage was 80 mV for an outdoor environment.