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.

Nanocomposites are materials of special interest for the development of flexible electronic, optical, and mechanical devices in applications such as transparent conductive electrodes and flexible electronic sensors. These materials take advantage of the electrical, chemical, and mechanical properties of a polymeric matrix, especially in force sensors, as well as the properties of a conductive filler such as silver nanowires (AgNWs). In this work, the fabrication of a force sensor using AgNWs synthesized via the polyol chemical technique is presented. The nanowires were deposited via drop-casting in polyvinyl alcohol (PVA) to form the active (electrode) and resistive (nanocomposite) sensor films, with both films separated by a cellulose acetate substrate. The dimensions of the resulting sensor are 35 mm × 40 mm × 0.1 mm. The sensor shows an applied force ranging from 0 to 3.92 N, with a sensitivity of 0.039 N. The sensor stand-off resistance, exceeding 50 MΩ, indicates a good ability to detect changes in applied force without an external force. Additionally, studies revealed a response time of 10 ms, stabilization of 9 s, and a degree of hysteresis of 1.9%. The voltage response of the sensor under flexion at an angle of 85° was measured, demonstrating its functionality over a prolonged period. The fabricated sensor can be used in applications that require measuring pressure on irregular surfaces or systems with limited space, such as for estimating movement in robot joints.

Copper (Cu) nanoparticles, known for their high electrical conductivity and cost-effectiveness, have emerged as essential materials in various applications from flexible electronics to antimicrobial agents. This work focuses on the synthesis and characterization of semiconductive nanostructured films composed of polyvinyl alcohol (PVA) with embedded Cu nanoparticles. The study provides a comprehensive analysis of the structural, optical, electrical, and dielectric properties of the resulting nanocomposites. The results indicate a significant reduction in optical band gap, from 4.82 eV in pure PVA to 2.6–2.8 eV in the nanocomposites, alongside enhanced electrical conductivities reaching 1.20 S/cm for films with 5 wt.% Cu. Dielectric assessments further reveal high dielectric constants, underscoring the potential of these materials for flexible electronic applications. This work highlights the effectiveness of incorporating Cu nanoparticles into polymer matrices, paving the way for advanced materials that meet the demands of next-generation electronics.

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.

The chapter deals with designing and implementing a flat filter regulation digital controller for a buck-boost DC-DC power converter. A highly perturbed, switched buck-boost power converter circuit is shown to be efficiently controlled in a regulation task for its non-minimum phase output using a suitable linear filter, addressed to as a flat filter. The flat filter control method is calculated from a transfer function, as in adaptive filtering control theory. It uses integral reconstructors regarding the input and output and finally employs partial state dynamics. Flat filtering is a natural, robust version of generalized proportional integral control (GPIC), by which the effects of arbitrary time-varying exogenous disturbances, unknown endogenous nonlinearities, and unmodeled dynamics can be jointly attenuated in a conceptually similar fashion to observer-based active disturbance rejection control (ADRC) and algebraic identification-based model-free control (MFC) but: a) without using linear extended state observers and b) respecting the original system order in a time-varying simplified model, while avoiding algebraic estimation techniques. The proposed control technique is implemented on the TMS320F28335 digital signal processor chip, with tests employing realistic simulations and an experimental setup.