Intelligent Electronic Systems Research Articles

Polyimide aerogel-based capacitive pressure sensor with enhanced sensitivity and temperature resistance

The development of intelligent electronic power systems necessitates advanced flexible pressure sensors. Despite improved compressibility through surface micro-structures or bulk pores, conventional capacitive pressure sensors face limitations due to their low dielectric constant and poor temperature tolerance of most elastomers. Herein, we constructed oriented polyimide-based aerogels with mechanical robustness and notable changes in dielectric constant under compression. The enhancement is attributed to the doping of surface-modified dielectric nanoparticles and graphene oxide sheets, which interact with polymer molecular chains. The resulting aerogels, with their excellent temperature resistance, were used to assemble high-performance capacitive pressure sensors. The sensor exhibits a maximum sensitivity of 1.41 kPa−1 over a wide working range of 0–200 kPa. Meanwhile, the sensor can operate in environments up to 150 °C during 2000 compression/release cycles. Furthermore, the aerogel-based sensor demonstrates proximity sensing capabilities, showing great potential for applications in non-contact sensing and extreme environment detection.

Preface

On behalf of the organizing committee, we are very pleased to introduce the proceedings of 2024 The 17th International Conference on Computer and Electrical Engineering (ICCEE 2024), which was held in Shenzhen, China (virtual) on June 28-30, 2024. Because more than two-thirds of the authors chose to attend the conference online, we had to switch to totally virtual conference to ensure the effectiveness of the conference. It is with great pleasure and anticipation that we convene once again to explore the latest advancements, challenges, and opportunities in the dynamic fields of Computer and Electrical Engineering. In today’s interconnected world, computer and electrical engineering play critical roles in shaping the technological landscape. ICCEE 2024 serves as a platform for fostering interdisciplinary collaboration, knowledge sharing, and networking among researchers, practitioners, and industry leaders. ICCEE 2024 lasted 3 days. There are online test sessions on ZOOM on the first day, and then followed with a wonderful array of 2 keynote speeches and 2 invited speeches, along with 4 technical sessions during June 29-30. The authors presentations cover topics on Power System Control Model and Simulation Analysis, Electrical Fault Detection and Maintenance Strategy, Digital Communication and Information Systems, Intelligent Electronic Systems and Status Monitoring, with 15 minutes for each presentation, including 2 minutes for the Q&A. Additionally, there are around 100 delegates attending online conference. Delegates had a wide range of sessions to choose from and had enough time in deciding which sessions to attend. List of Committee and Statement of Peer Review are available in this Pdf.

Optimization of resources in intelligent electronic health systems based on internet of things to predict heart diseases via artificial neural network

As a paradigm shift in tandem with the expansion of ICT, smart electronic health systems hold great promise for enhancing healthcare delivery and illness prevention efforts. These systems acquire an in-depth understanding of patient health states through the real-time collection and analysis of medical data enabled by the Internet of Things (IoT) and machine learning. With the widespread use of cutting-edge artificial intelligence and machine learning techniques, predictive analytics in medicine can assist in making the shift from a reactive to a proactive healthcare strategy. With the ability to rapidly and precisely evaluate massive amounts of data, draw intelligent conclusions, and solve difficult issues, artificial neural networks could revolutionize several industries. Two cardiac illnesses were assessed in this study using a multilayer perceptron artificial neural network that incorporated a genetic algorithm and an error-back propagation mechanism. The ability of artificial neural networks to handle consecutive time series data is crucial for optimizing resources in smart electronic health systems, especially with the increasing volume of patient information and the broad use of electronic clinical records. This requires the creation of more accurate predictive models. Through the use of Internet of Things (IoT) sensors, the proposed system gathers data, which is then used to do predictive analytics on patient history-related electronic clinical data saved in the cloud. A smart healthcare system that uses Mu-LTM (multidirectional long-term memory) to accurately monitor and predict the risk of heart disease has a coverage error of 97.94 %, an accuracy of 97.89 %, a sensitivity of 97.96 %, and a specificity of 97.99 %. In comparison to other smart heart disease prediction systems, the F1-score of 97.95 % and precision of 97.71 % is very good.

Implementation of a Trust-Based Framework for Substation Defense in the Smart Grid

The Smart Grid is a cyber-integrated power grid that manages electricity generation, transmission, and distribution to consumers and central to its functioning is the substation. However, integrating cyber-infrastructure into the substation has increased its attack surface. Notably, sophisticated attacks such as the PipeDream APT exploit multiple device protocols, such as Modbus, DNP3, and IEC61850. The substation’s constraints pose challenges for implementing security measures such as encryption and intrusion detection systems. To address this, we propose a comprehensive trust-based framework aimed at enhancing substation security. The framework comprises a trust model, a risk posture model, and a trust transferability model. The trust model detects protocol-based attacks on Intelligent Electronic Devices and SCADA HMI systems, while the risk posture model dynamically assesses the substation’s risk posture. The trust transferability model evaluates the feasibility of transferring and integrating a device and its trust capabilities into a different substation. The practical substation emulation involves a Docker-based testbed, employing a multi-agent architecture with a real-time Security Operations Center-influenced dashboard. Assessment involves testing against attacks guided by the MITRE ICS ATT&CK framework. Our framework displays resilience against diverse attacks, identifies malicious behavior, and rewards trustworthy devices.

Poly(arylene ether nitrile) composite foams with magnetically and electrically separated structures for frequency-selective electromagnetic interference shielding

With the rapid development of communication technology and modern intelligent electronic systems, the demand for frequency-selective electromagnetic interference (EMI) shielding materials has grown. In this work, poly(arylene ether nitrile) (PEN) composite foams with separated magnetic and conductive layers were prepared via delayed non-solvent induced phase separation, where the distribution of magnetic and conductive layers was designed to construct double-layer asymmetric structures and sandwich structures. Benefiting from destructive interference between electromagnetic waves (EMWs) in the magnetically and electrically separated porous structures, the double-layer asymmetric composites (M−C) exhibited outstanding absorption-dominated EMI shielding performance with favorable frequency selectivity, which did not occur in conventional double-layer composites. Specifically, M−C achieved a maximum shielding efficiency (SE) of 49.3 dB and a maximum average absorption ratio (Ar) of 93.9 %. Meanwhile, increasing the thickness of the magnetic layer of M−C can lower the characteristic frequency (fc) of the shielding peak and enhance average SE and average Ar. Moreover, M−C could show higher fc, average Ar, and average adsorption coefficient in the X-band when the incident EMWs first met with the magnetic layer, which was unavailable in frequency-selective PEN-based sandwich-structured composites. This effort offers a novel, flexible design to fabricate absorption-dominated EMI shielding materials with frequency selectivity.

Versatile spider-web-like cross-linked polyimide aerogel with tunable dielectric permittivity for highly sensitive flexible sensors

With the development of intelligent electronic power systems, the performance of flexible electronic sensors with portability and miniaturization is increasingly in demand. It is extremely challenging to achieve high modulus and high elasticity of polymer matrix simultaneously due to the inherent strength-elasticity conflict of elastic polymer. Here, a series of “spider-web-like” cross-linked polyimide aerogels (CPAs) had been successfully prepared. Benefiting from the robust dynamic network structure, the CPAs exhibited excellent compressive resilience, tunable dielectric permittivity, high thermal insulation property (λ = 0.040 W/m∙K) and modulus (E = 1073 KPa). Additionally, due to the excellent resilience of the CPAs and tunable permittivity, a CNTs/CPA-3 composite aerogel-based strain sensor obtained by assembling the CPA-3 with carbon nanotubes (CTNs) possessed synergistically enhanced sensitivity, high selectivity and “multi-touch” stress detection, without deterioration even after 2000 cycles. Furthermore, the established mathematical model revealed the internal mechanism of the synergistic enhancement of sensing performance of sensor with strain-controllable permittivity. Thus, the fabricated CPAs might be an ideal substrate material for flexible electronic sensors in electronic power systems, and the mathematical model established could also provide a reliable reference for improving the sensitivity and detection limits of sensors.

An artificial synapse based on La:BiFeO3 ferroelectric memristor for pain perceptual nociceptor emulation

Recently, memristors with brain-like synaptic behavior have attracted widespread attention, offering unprecedented opportunities for constructing future artificial intelligent bio-inspired electronic systems. Herein, we report a ferroelectric memristor with a Pd/La0.1Bi0.9FeO3(LBFO)/La0.67Sr0.33MnO3/SrTiO3/P+-Si structure, which exhibits the multilevel storage capacity of 12 resistive states, each with a retention time of 2 × 104 s and 200 ns ultra-fast pulse conductance modulation. Moreover, the synaptic properties are successfully mimicked, including paired-pulse facilitation, post-tetanic potentiation, and spike rate-dependent plasticity. In addition, pattern training with high tolerance to fault disturbance and variations is realized in the LBFO memristors array, endowing with highly accurate synaptic weights update capability. More importantly, the device can emulate essential characteristics of pain perception nociceptors with fast operating pulse and low threshold level, and a piezoresistive sensor is further introduced to integrate with LBFO memristor, realistically simulating the artificial pain perception function. Overall, the proposed device provides a promising avenue for the development of electronic skins, neurorobotics, and human–computer interaction technologies.

Design and Control of a Novel Wireless Energy Router With Independent Power Transmission Channels

Energy routers are intelligent power electronic systems that enable energy sharing and flexible power flow regulation among various distributed energy sources. Combining the excellent feature of wireless power transfer technology for contactless transmission of electrical energy, this article proposes a novel wireless energy router to realize the power exchange of multiple energy storage devices, such as various mobile electronics, electric vehicles, and energy storage stations. Independent power transmission channels with specific operating frequencies are built between any two of the power-exchanging units. The multiple resonating decoupling compensations are designed and implemented, which offer each power-exchanging unit and various resonate operating frequencies while suppressing the frequency components from irrelevant channels. Moreover, through generation by the bidirectional multilevel converter, the drive voltage of each unit can naturally realize the synthesis of multiple-frequency voltage components. In addition, the decoupled dual-side phase-shift control with capacitor voltage balancing strategy is proposed to regulate the power flow in each power channel. As a result, simultaneous energy sharing among power storage devices can be achieved. And the power flows can be adjusted independently without cross interference. Finally, both simulation and experimental results are presented to verify the effectiveness of the proposed wireless energy router.

Solution printable multifunctional polymer-based composites for smart electromagnetic interference shielding with tunable frequency and on–off selectivities

The advances in modern intelligent electronic systems have a pressing need for smart electromagnetic interference (EMI) shielding capabilities in a frequency-selective manner to choose which electromagnetic waves in a certain range to be blocked. Herein, we present multilayered EMI shielding composites that can provide selective on–off characteristics for specific frequency ranges across a broad spectrum. The composites are composed of outermost dielectric layers and conductive interlayers fabricated via solution printing, wherein hexagonal boron nitride (BN) and silver-coated BN particles are embedded, respectively. The EMI shielding frequency range and on–off selectivity are controllable by varying the configuration of the composite structure in terms of the BN content and the number of composite layers, providing different interstitial spaces between the fillers and interfacial dielectric properties. Furthermore, the optimal combination of these layers permits excellent combinatorial properties of EMI shielding effectiveness (32–62 dB), thermal conductivity (7.61 W/m·K), and electrical insulation (4.03 kV/mm) in the through-plane direction. The developed composites and their synthetic pathways have enormous potential for tailored material design and flexible system integration in next-generation EMI shielding technologies.

Ionic liquid-dispersed PDMS/SWCNT/Ag@Ni hybrid composite for temperature- and pressure-sensitive smart electromagnetic shielding applications

A thermally active ionic liquid (IL) impregnated composite was fabricated for thermally and mechanically controlled smart EMI shielding. Its versatility makes it a good choice for shielding high-end electronic and communication equipment.

Soft, Multifunctional, Robust Film Sensor Using a Ferroelectret with Significant Longitudinal and Transverse Piezoelectric Activity for Biomechanical Monitoring.

Soft and intelligent bioelectronics have achieved unprecedented development in both academics and industries over the last few decades, especially as ideal body-worn detectors for continuous human health status monitoring. However, the longstanding functional stability of bioelectronics in multiple environmental conditions of variant temperatures, humidities, and mechanical stimuli or even in some extremes, such as ultraviolet radiation and X-ray radiation, has confined the application of these electronics. Herein, a self-sustainable, multifunctional, robust sensor for biomechanical monitoring is prepared by hybridizing a parallel-tunnel fluorinated poly(ethylene propylene) (FEP) ferroelectret film (sensing layer) and poly(dimethylsiloxane) (PDMS, protection layer). A fast response (80 ms) and a low pressure detection limit (10 Pa) were achieved. Notably, the self-powered sensor can not only sensitively detect the loading of solid objects but also percept liquid water droplets and airflow, which satisfies the diverse needs of wearable devices. Meanwhile, the capability of stable and repeatable operation under a wide temperature range (-26-70 °C), extreme moisture, continuous mechanical stimulus (∼1.08 million cycles), and long-time ultraviolet radiation enabled the extensive and long-term application of such sensors in multiple scenarios. Moreover, the reproducibility of sensing performance after X-ray radiation can be realized through second contact polarization even after encapsulation. Due to the inherent mechanical flexibility, the fabricated sensor was conformally attached to rough and deformed skin and verified the feasibility of wearable biomechanical sensing with high sensitivity from facial smiling to plantar movement. This work provides an efficient strategy for multifunctional sensing, holding great promise for advanced soft bioelectronics in the next generation of wearable intelligent electronic systems.

A light-weight, thin-thickness, flexible multifunctional electrochromic device integrated with variable optical, thermal management and energy storage

Multifunctional electrochromic devices with diversified functions are highly desirable for intelligent electronic systems compared to conventional electrochromic devices with sole applicability. Herein, a multifunctional electrochromic device integrated with variable optical, thermal management and energy storage is realized by preparing nanowire‐structured coral-like PANI films on a flexible gold-plated membrane through the combination of galvanostatic and cyclic voltammetric electrodeposition techniques. The multifunctional electrochromic devices achieve reversible color changes between brownish-yellow, green and dark-green. The maximum emissivity changes of the multifunctional electrochromic device in the ranges of 3–5 μm, 8–14 μm and 2.5–15 μm are 0.42, 0.49 and 0.47, respectively. Moreover, a specific capacitance of 355 F g−1 is obtained for the multifunctional electrochromic devices at a current density of 1 A g−1. The multifunctional electrochromic devices also have such advantages as light-weight, thin-thickness, flexible and can be fabricated in a multipixel and large area. With versatility characteristics, the multifunctional electrochromic devices are highly promising for intelligent electronic systems in electronic clothing, military camouflage and thermal control system of spacesuits.

Multi-functional and integrated actuators made with bio-inspired cobweb carbon nanotube–Polymer composites

Soft actuators have emerged as flexible platforms that can integrate many functional electronic devices to build intelligent electronic systems. The energy supply and wireless signal transmission of electronic systems of the multi-functional actuators are challenging research areas. Here, the idea of the functionalized and hierarchical design is proposed to construct the multi-functional and integrated actuators. Inspired by the structure of cobwebs, multi-functional carbon nanotube (CNT)-polymer composites with network structures are proposed and applied in multi-responsive actuators, supercapacitors, and electromagnetic interference (EMI) shielding devices. Two multi-functional and integrated actuators are highlighted to demonstrate the practical applications. One is a light-driven actuator integrated with an EMI shielding function, which can be used as an intelligent shielding curtain. The other is an electrical-driven actuator integrated with an energy storage function. Especially, the functions of actuation and energy storage can be simultaneously/independently used without interfering with each other. We provide comprehensive research from the material level (CNT-polymer composites) to the device level (actuators, supercapacitors, EMI shielding devices), and then to the system level (multi-functional actuators). We believe that the integration design of the multi-functional actuators will open up new avenues for the development of soft robotics, wireless signal transmission switch, and deformable supercapacitors.

Safe Detection of Wheels Spinning and Sliding in Vehicles

The vehicle industry’s primary theme is the increase in automating and integrating more robust intelligent electronic systems to transform towards Industry 4.0, enhance safe functioning with more flexibility, and extend the virtual productive age of the vehicular systems. Further, significant efforts focus on developing monitoring systems for abnormal driving conditions such as wheel spinning and sliding that can increase the operating environment’s hazards and speed up the wearing-off process. Thus, these events play a primary role in influencing the safety of the involved humans and determining the vehicle’s lifespan and the incurred maintenance costs because of the encumbrances by the generated vibrations and shocks. However, the existing measurement systems are not entirely digitized, and their initial development did not concern the concept of functional safety like redundancy to be used in safety-critical environments. Further, the current systems depend on a costly sensory system that requires strict and complex installation procedures. Therefore, the prevention of wheel spinning and sliding events by a safety-related miniaturized digital intelligent monitoring system comes to a corresponding meaning. Accordingly, this research work investigates the development of a novel safety-related platform following the standard IEC 61508 for monitoring and controlling abnormal driving conditions through vibration sensors incorporated with rotation sensors. The research work tests the novel system on a prototype vehicle where the conducted experiments prove the system’s capability to detect the events with reasonable accuracy. Further, this novel approach’s evaluation shows that the system represents a significant enhancement for various similar researches and applications.

Small-Size Algorithms for the Type-I Discrete Cosine Transform with Reduced Complexity

Discrete cosine transforms (DCTs) are widely used in intelligent electronic systems for data storage, processing, and transmission. The popularity of using these transformations, on the one hand, is explained by their unique properties and, on the other hand, by the availability of fast algorithms that minimize the computational and hardware complexity of their implementation. The type-I DCT has so far been perhaps the least popular, and there have been practically no publications on fast algorithms for its implementation. However, at present the situation has changed; therefore, the development of effective methods for implementing this type of DCT becomes an urgent task. This article proposes several algorithmic solutions for implementing type-I DCTs. A set of type-I DCT algorithms for small lengths N=2,3,4,5,6,7,8 is presented. The effectiveness of the proposed solutions is due to the possibility of fortunate factorization of the small-size DCT-I matrices, which reduces the complexity of implementing transformations of this type.

Magnetic flexible sensor with tension and bending discriminating detection

The flexible wearable sensors with high sensitivity and stability provide wide potential in artificial intelligence and human–machine interaction. However, dual-modal sensor with contact and non-contact working mode based on a facile and cost-effective methodology which can recognize external stimulus forms remains a challenge. Especially, magnetic non-contact sensing performance has gained increasing attention in smart wearable device. This work reports a flexible and magnetic sensor based on a sandwich structure film (SSF) which can detect both tension and bending stimuli by supplementing opposite electric signal feedbacks. Notably, the ΔR/R0 of SSF sensor reaches 44.1% at 5% tensile strain and it presents excellent stability even after 10,000 cycles. Moreover, the ΔR/R0 of SSF sensor maintains at −17.2% under 2 mm bending displacement. Additionally, SSF sensor can be employed as electronic skin to perceive the human joint motion in real-time. Furthermore, the direction and density of magnetic field applied to SSF sensor can be clearly discriminated, thus a non-contact magnetic keyboard has been designed and developed. As a result, the facile manufacturing processes and outstanding multifunctional sensing characteristics endow SSF sensor with high implementation potential in the next-generation intelligent electronic equipment or systems.

A review of harmonization methods for studying dietary patterns.

Data harmonization is the process by which each of the variables from different research studies are standardized to similar units resulting in comparable datasets. These data may be integrated for more powerful and accurate examination and prediction of outcomes for use in the intelligent and smart electronic health software programs and systems. Prospective harmonization is performed when researchers create guidelines for gathering and managing the data before data collection begins. In contrast, retrospective harmonization is performed by pooling previously collected data from various studies using expert domain knowledge to identify and translate variables. In nutritional epidemiology, dietary data harmonization is often necessary to construct the nutrient and food databases necessary to answer complex research questions and develop effective public health policy. In this paper, we review methods for effective data harmonization, including developing a harmonization plan, which common standards already exist for harmonization, and defining variables needed to harmonize datasets. Currently, several large-scale studies maintain harmonized nutrient databases, especially in Europe, and steps have been proposed to inform the retrospective harmonization process. As an example, data harmonization methods are applied to several U.S longitudinal diet datasets. Based on our review, considerations for future dietary data harmonization include user agreements for sharing private data among participating studies, defining variables and data dictionaries that accurately map variables among studies, and the use of secure data storage servers to maintain privacy. These considerations establish necessary components of harmonized data for smart health applications which can promote healthier eating and provide greater insights into the effect of dietary patterns on health.

Digital Pole Control for Speed and Torque Variation in an Axial Flux Motor with Permanent Magnets

The use of renewable energies in the transportation industry has prompted the development of higher power electric motors and intelligent electronic traction systems. However, the typical coupling between the two continues to be mechanical, which reduces its efficiency and useful life. On the other hand, permanent magnet axial flux motor configurations make it possible to dispense with mechanical couplings, due to their high torque at low speeds due to their direct application on the wheels of vehicles. In this work, the design of a digital pole commutation system is presented, applied to an axial flux motor with permanent magnets for speed and torque control at a constant speed. The performance of the system is evaluated with experimental measurements; proving the effectiveness of the design, obtaining torques of up to 1784 Nm without extra mechanical couplings and maximum speed regulation errors of 8.43%.

All-in-One ENERGISER design: Smart liquid metal-air battery

Self-powered integration is an effective way of promoting efficiency and miniaturizing in portable intelligent electronic systems. Conventional battery design focuses on the improvement of charge–discharge property, and energy storage units usually design independently from energy consumption units including sensing or transmitting device. Here, an unusual battery design in which the batteries possess the function of energy storage, sensing, and signal transducer, called all-in-one ENERGISER, is integrated for the first time, which is realized by fabricating a gallium-based liquid metal-air battery (LMAB) without any other extra electronic components. Gallium-based liquid metals (LMs) wetted on the coppered-coated carbon fibers act as anode and air electrode acts as the cathode, the chemical activity of LMs and the sensitivity of gallium oxide layer are utilized for sensing function. For the discharge performance of LMABs, the energy density of LMABs changes from 1.52 to 0.79 mWh/cm2 while the corresponding power densities range from 0.36 to 2.05 mW/cm2. Additionally, the function of sensing environmental parameters achieves selectively detecting main components of air and distinguishing liquid type. Remarkably, the physical signals, such as humidity, is converted into low and high-potential signals, and further encoded into digital signals. Eventually, the all-in-one battery strategy is validated and shows excellent energy storage capacity, marvelous sensing function, and superb signal transmitting activity. The all-in-one battery design concept may open up a new direction for the exploitation of state-of-the-art functional and highly integrated battery.

Artificial Skin Perception.

Skin is the largest organ, with the functionalities of protection, regulation, and sensation. The emulation of human skin via flexible and stretchable electronics gives rise to electronic skin (e-skin), which has realized artificial sensation and other functions that cannot be achieved by conventional electronics. To date, tremendous progress has been made in data acquisition and transmission for e-skin systems, while the implementation of perception within systems, that is, sensory data processing, is still in its infancy. Integrating the perception functionality into a flexible and stretchable sensing system, namely artificial skin perception, is critical to endow current e-skin systems with higher intelligence. Here, recent progress in the design and fabrication of artificial skin perception devices and systems is summarized, and challenges and prospects are discussed. The strategies for implementing artificial skin perception utilize either conventional silicon-based circuits or novel flexible computing devices such as memristive devices and synaptic transistors, which enable artificial skin to surpass human skin, with a distributed, low-latency, and energy-efficient information-processing ability. In future, artificial skin perception would be a new enabling technology to construct next-generation intelligent electronic devices and systems for advanced applications, such as robotic surgery, rehabilitation, and prosthetics.