Internet of Things: A Review on Theory Based Impedance Matching Techniques for Energy Efficient RF Systems

Reliability Analysis and Optimization of a Reconfigurable Matching Network for Communication and Sensing Antennas in Dynamic Environments through Gaussian Process Regression

During the implementation of the Internet of Things (IoT), the performance of communication and sensing antennas that are embedded in smart surfaces or smart devices can be affected by objects in their reactive near field due to detuning and antenna mismatch. Matching networks have been proposed to re-establish impedance matching when antennas become detuned due to environmental factors. In this work, the change in the reflection coefficient at the antenna, due to the presence of objects, is first characterized as a function of the frequency and object distance by applying Gaussian process regression on experimental data. Based on this characterization, for random object positions, it is shown through simulation that a dynamic environment can lower the reliability of a matching network by up to 90%, depending on the type of object, the probability distribution of the object distance, and the required bandwidth. As an alternative to complex and power-consuming real-time adaptive matching, a new, resilient network tuning strategy is proposed that takes into account these random variations. This new approach increases the reliability of the system by 10% to 40% in these dynamic environment scenarios.

Coexistence of large-area topological pseudospin and valley states in a tri-band heterostructure system

The rapid development of topological photonics has significantly revolutionized our comprehension of electromagnetic wave manipulation in recent decades. Recent research exploiting large-area topological states inserts an additional gapless PC structure between topologically trivial and nontrivial PCs, effectively introducing the mode width degree of freedom. Nevertheless, these heterostructures mainly support only single-type waveguide states operating within a single frequency band. To address these limitations, we propose a novel, to the best of our knowledge, tri-band three-layer heterostructure system, supporting both large-area pseudospin- and valley-locked states. The system showcases tunable mode widths with different operational bandwidths. Moreover, the heterostructures exhibit inherent topological characteristics and reflection-free interfacing, which are verified in the well-designed Z-shaped channels. The proposed heterostructure system can be used to design multi-band multi-functional high-flexibility topological devices, providing great advantages for enlarging the on-chip integrated communication systems.

Progress of Materials and Devices for Neuromorphic Vision Sensors

The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords: smaller, faster, and smarter. (1) Smaller: Devices are becoming more compact by integrating previously separated components such as sensors, memory, and processing units. As a prime example, the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits, such as simpler circuitry, lower power consumption, and less data redundancy. (2) Swifter: Owing to the nature of physics, smaller and more integrated devices can detect, process, and react to input more quickly. In addition, the methods for sensing and processing optical information using various materials (such as oxide semiconductors) are evolving. (3) Smarter: Owing to these two main research directions, we can expect advanced applications such as adaptive vision sensors, collision sensors, and nociceptive sensors. This review mainly focuses on the recent progress, working mechanisms, image pre-processing techniques, and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.

Internet of Things: Development Intelligent Programmable IoT Controller for Emerging Industry Applications

The Internet of Things (IoT) has become critical to the implementation of Industry 4.0. The successful operation of smart manufacturing depends on the ability to connect everything together. In this research, we applied the TOC (Theory of Constraints) to develop a wireless Wi-Fi intelligent programmable IoT controller that can be connected to and easily control PLCs. By applying the TOC-focused thinking steps to break through their original limitations, the development process guides the user to use the powerful and simple flow language process control syntax to efficiently connect to PLCs and realize the full range of IoT applications. Finally, this research uses oil–water mixer equipment as the target of continuous improvement and verification. The verification results meet the requirements of the default function. The IoT controller developed in this research uses a marine boiler to illustrate the application. The successful development of flow control language by TOC in this research will enable academic research on PLC-derivative applications. The results of this research will help more SMEs to move into smart manufacturing and the new realm of Industry 4.0.

Theoretical and Empirical Verification of Electrical Impedance Matching Method for High-Power Transducers

In our prior study, a systematic approach was used to devise Langevin transducers for high-power applications where the energy efficiency was not considered in the design criteria. In this paper, the impedance matching methods are thus proposed to evaluate what matching topology is appropriate for their use. Both the series inductor scheme and low pass filter composed of a series inductor and shunt capacitor are examined as matching circuits. According to MATLAB simulation, the resonance frequency is seen at 36.79 kHz due to a series L circuit, and its associated impedance is reduced by 70.45% from that of its non-matching condition. The measured resonance frequency is 36.77 kHz and the corresponding impedance is decreased by 59.52%. Furthermore, the acoustic pressure is measured to determine the effect of the matching circuit on the transducer’s actual behavior. The transducer with a series L circuit shows more efficient matching results, 2.28 kPa of positive acoustic pressure is emitted without matching and 3.35 kPa is emitted with a series L element, respectively. As a result, this study demonstrates how to evaluate the influence of matching circuits by using our customized approach rather than commercial SPICE programs, as well as how to experimentally verify the acoustic behavior of high-power Langevin transducers.