Intelligent Devices Research Articles

Advanced testbed to assess disturbances in electrical grids with DERs using relays/meters with varying sampling frequencies

Distributed energy resources (DERs) are vital to achieve clean energy goals, but in some cases, their rapid deployment has led to negative effects on their reliability because of possible voltages and/or current disturbances that need to be analyzed in detail. This study created an advanced testbed with a real-time simulator and synchronized time and trigger event systems was created to compare event disturbances from intelligent electronic devices (IEDs) with different sampling frequencies and locations in an electrical grid containing DERs. This testbed is capable of capturing the recorded events of multiple IEDs and the real-time simulator to assess the effect of the disturbances and IEDs’ behaviors, including phase voltages, phase current waveforms, and total harmonic distortion (THD) analysis. In this study, a three-line-to-ground electrical fault was simulated, the disturbance event was detected, and recorded events (from 4 to 133 samples per cycle) were collected from meters and relays located at different sites. A harmonic peak algorithm, which was based on measuring the phase voltage and phase current THD peaks at the first one-cycle of the disturbance events, was created to assess and detect the fault states and locations. Several important findings resulted from performing this study, such as selecting IEDs with high sampling frequencies, installing all IEDs with similar sampling frequencies, assessing the software limitations for computing THD, studying the effect of the IEDs’ locations (downstream or upstream) with respect to the electrical fault site and the distance from the disturbance event point, evaluating the percentage errors of the phase voltage THD peaks at the first one-cycle of disturbance events, and installing synchronized time source and trigger event signal systems for recording the IEDs’ events.

Intelligent devices for assessing essential tremor: a comprehensive review.

Essential tremor (ET) stands as the most prevalent movement disorder, characterized by rhythmic and involuntary shaking of body parts. Achieving an accurate and comprehensive assessment of tremor severity is crucial for effectively diagnosing and managing ET. Traditional methods rely on clinical observation and rating scales, which may introduce subjective biases and hinder continuous evaluation of disease progression. Recent research has explored new approaches to quantifying ET. A promising method involves the use of intelligent devices to facilitate objective and quantitative measurements. These devices include inertial measurement units, electromyography, video equipment, and electronic handwriting boards, and more. Their deployment enables real-time monitoring of human activity data, featuring portability and efficiency. This capability allows for more extensive research in this field and supports the shift from in-lab/clinic to in-home monitoring of ET symptoms. Therefore, this review provides an in-depth analysis of the application, current development, potential characteristics, and roles of intelligent devices in assessing ET.

Experimental investigation and intelligent control of the magnus anti-rolling device for ship stability at zero speed

Under zero-speed conditions, ships are particularly susceptible to the effects of waves, which directly impact the safety of the vessel. A ship anti-rolling device based on the Magnus effect is designed to mitigate rolling motions across a full range of speeds, thereby enhancing the vessel's stability. This study presents an experimental investigation and intelligent control of Magnus anti-rolling devices aimed at enhancing ship stability at zero speed. The test setup, intelligent control algorithm, and experimental procedures specifically tailored for evaluating the Magnus anti-rolling device were designed. Following this, a comprehensive analysis was conducted to assess the effects of different cylinder geometries, swinging speeds, initial roll angles, and control methods on the anti-rolling characteristics of the device. Results demonstrate that the intelligent control method achieves an average anti-rolling efficiency of 89%. Additionally, the optimised geometric model of the Magnus anti-rolling device exhibits improved anti-rolling efficiency relative to the original model. The study confirms the stability and robustness of the intelligent Magnus anti-rolling device and suggests future research directions for practical applications aboard full-scale vessels in complex marine environments.

FedCrow: Federated-Learning-Based Data Privacy Preservation in Crowd Sensing

In the process of completing large-scale and fine-grained sensing tasks for the new generation of crowd-sensing systems, the role of analysis, reasoning, and decision making based on artificial intelligence has become indispensable. Mobile crowd sensing, which is an open system reliant on the broad participation of mobile intelligent terminal devices in data sensing and computation, poses a significant risk of user privacy data leakage. To mitigate the data security threats that arise from malicious users in federated learning and the constraints of end devices in crowd-sensing applications, which are unsuitable for high computational overheads associated with traditional cryptographic security mechanisms, we propose FedCrow, which is a federated-learning-based approach for protecting crowd-sensing data that integrates federated learning with crowd sensing. FedCrow enables the training of artificial intelligence models on multiple user devices without the need to upload user data to a central server, thus mitigating the risk of crowd-sensing user data leakage. To address security vulnerabilities in the model data during the interaction process in federated learning, the system employs encryption methods suitable for crowd-sensing applications to ensure secure data transmission during the training process, thereby establishing a secure federated-learning framework for protecting crowd-sensing data. To combat potential malicious users in federated learning, a legitimate user identification method based on the user contribution level was designed using the gradient similarity principle. By filtering out malicious users, the system reduces the threat of attacks, thereby enhancing the system accuracy and security. Through various attack experiments, the system’s ability to defend against malicious user attacks was validated. The experimental results demonstrate the method’s effectiveness in countering common attacks in federated learning. Additionally, through comparative experiments, suitable encryption methods based on the size of the data in crowd-sensing applications were identified to effectively protect the data security during transmission.

Spatial evolution of the proton-coupled Mott transition in correlated oxides for neuromorphic computing.

The proton-electron coupling effect induces rich spectrums of electronic states in correlated oxides, opening tempting opportunities for exploring novel devices with multifunctions. Here, via modest Pt-aided hydrogen spillover at room temperature, amounts of protons are introduced into SmNiO3-based devices. In situ structural characterizations together with first-principles calculation reveal that the local Mott transition is reversibly driven by migration and redistribution of the predoped protons. The accompanying giant resistance change results in excellent memristive behaviors under ultralow electric fields. Hierarchical tree-like memory states, an instinct displayed in bio-synapses, are further realized in the devices by spatially varying the proton concentration with electric pulses, showing great promise in artificial neural networks for solving intricate problems. Our research demonstrates the direct and effective control of proton evolution using extremely low electric field, offering an alternative pathway for modifying the functionalities of correlated oxides and constructing low-power consumption intelligent devices and neural network circuits.

Optimal deployment of private 5G multi-access edge computing systems at smart factories: Using hybrid crow search algorithm

In smart factories, an increasing number of mobile intelligent devices are deployed to meet the growing demands for flexible manufacturing. These devices, equipped with various sensors, synchronize a substantial amount of data with cloud servers for real-time monitoring and control. Fifth generation mobile networks (5G) combined with multi-access edge computing (MEC) provide the capabilities for multiple connections, large-scale data transmission, and efficient response times, becoming the mainstream network architectures for the needs. Additionally, with the emerging trend of energy-saving, recent works have addressed energy consumption as a significant cost factor. However, most previous studies tended to focus solely on cloud servers, neglecting energy consumption at edge computing and underestimating the impact of heterogeneous mobile device. As the scope of smart factory networks continues to expand, the challenges become increasingly critical. This study presents a private 5G MEC system architecture tailored for smart panel factories. The concerned problem is formulated as an integer programming model, which determines deployment locations and quantities for MEC servers and 5G small cells, including picocells and femtocells, so as to minimize the overall deployment costs while meeting the constraints of connectivity, capacity, latency, coverage, serviceability, and energy consumption. Since the edge server deployment problem is NP-hard, this study further proposes a hybrid metaheuristic algorithm, CSAVNS, which combines the strengths of crow search algorithm (CSA) and variable neighborhood search (VNS). In the global search phase of CSA, the VNS local search is introduced to enhance the algorithm's capabilities. Experimental analysis demonstrates that the proposed CSAVNS outperforms other algorithms in terms of solution solving capabilities.

Safety and Efficacy of Dry Eye Intelligent Therapeutic Device in the Treatment of Meibomian Gland Dysfunction in Rabbits

Purpose To assess the safety and efficacy of the dry eye intelligent therapeutic device in rabbits with meibomian gland dysfunction. Methods The meibomian gland dysfunction-afflicted rabbits were subjected to treatment using the dry eye intelligent therapeutic device. Various parameters, including eyelid margin, meibomian gland opening, redness, meibomian gland area, keratoconjunctival fluorescence staining, and intraocular pressure, were examined and analyzed using an ocular surface comprehensive examination instrument, slit lamp, and tonometer at corresponding times points. Hematoxylin and eosin staining was performed to examine the mucosal epithelium and meibomian gland. Results In this study, eyelid margin congestion and meibomian gland opening obstruction were significantly improved after 3 weeks and 4 weeks of treatment, respectively (p < .01, p < .05). The treatment group showed a significant increase in tear meniscus height after 2 weeks, 3 weeks and 4 weeks of treatment (p < .001, p < .01, p < .05). No significant changes were noted in meibomian gland area, redness, intraocular pressure, and keratoconjunctival fluorescence staining of rabbits before and after treatment. Hematoxylin and eosin staining revealed a complete structure of mucosal epithelium and meibomian gland in the treatment group and that the expansion of the blocked meibomian gland duct was reduced. Conclusion The utilization of the dry eye intelligent therapeutic device in treating meibomian gland dysfunction-afflicted rabbits exhibits potential promising safety, efficacy, and overall benefits, thereby offering a novel alternative for managing meibomian gland dysfunction patients in clinical settings.

All-inorganic ultrathin high-sensitivity transparent temperature sensor based on a Mn-Co-Ni-O nanofilm

The demand for optically transparent temperature sensors in intelligent devices is increasing. However, the performance of these sensors, particularly in terms of their sensitivity and resolution, must be further enhanced. This study introduces a novel transparent and highly sensitive temperature sensor characterized by its ultrathin, freestanding design based on a Mn-Co-Ni-O nanofilm. The Mn-Co-Ni-O-based sensor exhibits remarkable sensitivity, with a temperature coefficient of resistance of −4% °C−1, and can detect minuscule temperature fluctuations as small as 0.03 °C. Additionally, the freestanding sensor can be transferred onto any substrate for versatile application while maintaining robust structural stability and excellent resistance to interference, indicating its suitability for operation in challenging environments. Its practical utility in monitoring the surface temperature of optical devices is demonstrated through vertical integration of the sensor and a micro light-emitting diode on a polyimide substrate. Moreover, an experiment in which the sensor is implanted in rats confirms its favorable biocompatibility, highlighting the promising applications of the sensor in the biomedical domain.

Hygro‐Dynamic and Conductive Actuator That Restructures and Heals by Water

AbstractThe prospects of endowing stimuli‐responsive materials with various life‐like behaviors are promoting the development of intelligent robotic and electronic devices. However, it is challenging to incorporate stimuli‐responsive actuating and healing capabilities into one single material system. Herein, the design and assembly of humidity‐responsive thin films composed of poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) and sodium carboxymethyl cellulose (NaCMC) forming a conducting polymer composite through a physically cross‐linked and hydrogen‐bonded supramolecular network are described. Owing to its enhanced dynamics of hydrogen bonding at an elevated humidity, the PEDOT:PSS/NaCMC thin film exhibits a rapid humidity‐responsive actuating performance in an environment with humidity gradient, as well as a repairing function of the structural, mechanical, electrical, and actuating properties after being damaged through a humidifying‐drying cycle. Based on a combined analytical approach, a structural model is proposed for the rearrangement of the thin film when being exposed to stepwise humidity levels at multi‐length scales. Due to the structural rearrangement powered by humidity variations, the film exhibits tunable actuating and healing performance, which makes it a promising candidate material for applications in intelligent soft robotics such as artificial muscles.

Shape Dependence of Photoresponsive Molecular Crystals Composed of Naphthyl Acrylic Acid Stimulated by Solid-State [2 + 2] Photocycloaddition

Photomechanical molecular crystals, actuated by solid-state photochemical reactions, manifest a spectrum of mechanical motions upon light exposure, underscoring their prospective integration into the next generation of intelligent materials and devices. Utilizing the solid-state photodimerization of naphthyl acrylic acid as a paradigm, this study delved into the interplay between crystal morphology and reaction dynamics on the photomechanical responses of molecular crystals. Distinct crystal forms—bulk, microrods, and microplates—were cultivated through tailored crystallization conditions. While bulk crystals of naphthyl acrylic acid (NA) underwent shattering and splintering upon UV light exposure, the microplate counterparts displayed unique cracking patterns with fissures yet retained their overall structural integrity. In contrast, NA microrods underwent pronounced bending under identical irradiation conditions. These phenomena are attributed to the efficient lattice reconfiguration stemming from the [2 + 2] cycloaddition photochemical reaction within the crystals. An intermediate fluorescence enhancement was observed across all crystal types upon light exposure. Collectively, our results underscore the pivotal role of crystal shape in dictating photomechanical behavior, thereby heralding novel strategies for developing advanced photomechanical materials.

Lithium-Ion-Doped Eutectogel for Surface-Capacitive Sensing Touch Panel.

Touch panels are deemed as a critical platform for the future of human--computer interaction. Recently, flexible touch panels have attracted much attention due to their superior adhesivity and integratability to the human body. However, hydrogel- or organogel-based devices suffer from instability due to liquid evaporation or low-conductivity substrates. It demands an alternative functional touch panel featuring temperature tolerance, high conductivity, and stretchability. Here, we introduce an eutectogel by immobilizing a novel deep eutectic solvent (DES) within 2-hydroxyethyl acrylate (HEA) covalently cross-linked polymer scaffolds. In this DES (ethylene carbonate(EC)-LiTFSI), the C═O group of EC is unique as an electron donor exhibiting strong coordination interactions with Li+, promoting the dissociation of Li+ from LiTFSI to achieve excellent conductivity. Benefiting from their traits, eutectogel presents high conductivity, transmittance, antifreezing, and mechanical strength. In addition, using the surface-capacitive sensing mechanism, the eutectogel can be designed as a 1D strip and 2D rectangular touch panel which can achieve high-resolution touching tracks, even in a low-temperature environment and pressure-then-recovered state. This eutectogel strategy is envisioned to facilitate the development of next-generation intelligent devices, especially in extreme stretching and low-temperature application scenarios.

Protecting the patient’s data in the 21st century healthcare industry: Is the African continent ready for the digital space?

To ensure proper healthcare services and automation, including minimising medical errors and providing faster and more efficient healthcare, the medical field is experiencing innovative technological trends. They include automated patient records, hospital management system software, telemedicine, and the use of artificial intelligence devices. These innovations exist in more than just the global north, as they are slowly finding residence in African countries. Focusing on automated patient record, the article examines existing data protection legal frameworks in Africa to ascertain whether they provide effective remedy mechanisms patients can access should a breach occur. Taking cognisance of the current African Continental Free Trade Area Agreement (AfCFTA) aimed at creating a single market for goods and services; it is evident that healthcare services might have a continental approach. Thus, the article adopts a continental, regional, and national perspective. Using doctrinal method, the article compares the African Union Data Protection Convention with the European Union General Data Protection Regulation to draw lessons from the European Union Experience. The article finds that strengthened national mechanisms might provide the requisite remedy mechanisms patients can access to ensure enforcement of their rights to data protection.

A Smart Self‐Healing Material with Reversible Optical, Mechanical, and Electrical Transition Induced by Humidity and Temperature

AbstractSmart responsive materials that can alter their function in response to environmental changes are attractive for their potential applications in intelligent devices and products. Herein, a smart material that exhibits reversible changes in multiple properties upon variations in humidity or temperature is created. The material spontaneously transits between hydrated and dehydrated states in response to fluctuations in the surrounding humidity or temperature. Consisting of a mixture of poly(propylene glycol) (PPG) with urea linkages (PPGurea) and ionic liquid [EMIM][TFSI], the transition is attributed to a series of synergetic interactions among various chemical components and groups, including ether‐cation coordination, water‐anion complex, urea‐urea bidentate hydrogen bonds, and cation–anion electrostatic interactions. In the hydrated state, with a very small amount (4–5 wt%) of spontaneously absorbed moisture content, the smart material is soft, transparent, and conductive, and possesses rapid self‐healing ability. Upon dehydration, the material transits into a phase‐separated system with PPG‐rich and IL‐rich phases, resulting in opacity, severely reduced ionic conductivity, yet significantly enhanced stiffness, strength, and toughness. The drastic change in multiple properties makes it an intelligent material well‐suited for various smart applications such as sensors, 3D printed optoelectronics and smart windows, which can automatically alter their functions to adapt to environmental changes.

Biodegradable flexible triboelectric nanogenerator for winter sports monitoring

With the energy crisis and environmental pollution becoming a growing concern worldwide, the development of clean and renewable energy from the environment has become an imperative for human survival and development. However, the equipment used to harvest clean renewable energy is large, subject to environmental impacts and regional differences (such as wind, solar and tidal energy). In this study, a biodegradable eggshell membrane triboelectric nanogenerator (EM-TENG) is introduced for the purpose of harvesting low-frequency mechanical energy. A Wireless Intelligent Motion Monitoring System (WIMMS) has been created using EM-TENG. It includes a Bluetooth sensor terminal and an intelligent processing terminal for digital signal reception on a host computer. The EM-TENG can be attached to knee and ankle joints to monitor posture. Therefore, for real-time monitoring of joint and kinetic chain changes during land training of ice dance athletes, the intelligent ice dance land training aid system is important. As a wearable motion monitoring sensor, EM-TENGs application in intelligent motion monitoring, intelligent wearable devices and big data analytics is being promoted.

Detection of Ascorbic Acid by Two-Dimensional Conductive Metal-Organic Framework-Based Electrochemical Sensors.

The realization of efficient and accurate detection of biomolecules has become a key scientific issue in the field of life sciences. With the rapid development of nanotechnology, electrochemical sensors constructed from the superior physical and chemical properties of nanomaterials show faster and more accurate detection. Among nanomaterials, two-dimensional conductive MOF (2D cMOF) is considered to be a star material in electrochemical sensors due to its remarkable conductivity, high porosity, and stability. In this paper, a Cu3(HHTP)2/SPE electrochemical sensor for the detection of ascorbic acid (AA) was constructed by modifying 2D cMOF (Cu3(HHTP)2) on the surface of the screen-printed electrode (SPE). The sensor exhibited excellent catalytic activity in the detection of AA, with a lower detection limit of 2.4 μmol/L (S/N = 3) and a wide linear range of 25-1645 μmol/L. This high catalytic activity can be attributed to the abundant catalytic sites in Cu3(HHTP)2 and the rapid electron transfer between Cu+ and Cu2+, which accelerates the oxidation of AA. This work lays a foundation for the subsequent development of MOFs with special electrochemical catalytic properties and the integration of 2D cMOF into intelligent electrical analysis devices.

Tough bilayer thermo‐responsive hydrogel actuator reinforced by Fe3+ complexation

AbstractHydrogel actuators usually suffer from the poor mechanical property, which hinders their wide applications. In this study, we propose a tough bilayer hydrogel actuator that can respond quickly to temperature. The hydrogels are composed of poly(N‐isopropylacylamide) (PNIPAM) layer and poly(acrylamide‐co‐acrylic acid) (P(AAm‐co‐AAc)) layer strengthened through Fe3+ complexation with carboxyl groups. By optimizing the PNIPAM content, the resulting bilayer hydrogel P(NIPAM0.9/AAm‐co‐AAc)‐Fe3+ exhibits fast and large‐amplitude bending and recovery in response to temperature. It also shows excellent mechanical properties with a tensile strength of 2.54 MPa, tensile modulus of 3.7 MPa, and toughness of 9.4 MJ/m3, respectively. Besides, the multiple noncovalent interactions within the hydrogels, including Fe+‐mediated coordination and hydrogen bonds, can serve as dynamic but stable associations, leading to a good self‐healing ability. The bilayer hydrogel is further made into a gripper that can effectively and sensitively respond to temperature to capture and release an object, showing its potential application in artificial intelligent devices.

Additive Manufacturing Provides Infinite Possibilities for Self-Sensing Technology.

Integrating sensors and other functional parts in one device can enable a new generation of integrated intelligent devices that can perform self-sensing and monitoring autonomously. Applications include buildings that detect and repair damage, robots that monitor conditions and perform real-time correction and reconstruction, aircraft capable of real-time perception of the internal and external environment, and medical devices and prosthetics with a realistic sense of touch. Although integrating sensors and other functional parts into self-sensing intelligent devices has become increasingly common, additive manufacturing has only been marginally explored. This review focuses on additive manufacturing integrated design, printing equipment, and printable materials and stuctures. The importance of the material, structure, and function of integrated manufacturing are highlighted. The study summarizes current challenges to be addressed and provides suggestions for future development directions.

An Intelligent Non-Invasive Blood Pressure Monitoring System Based on a Novel Polyvinylidene Fluoride Piezoelectric Thin Film.

Hypertension is a common cause of cardiovascular diseases, closely associated with the high mortality and disability rates of cardiovascular diseases such as stroke and coronary heart disease. Therefore, developing a comfortable and sustainable device for monitoring human pulse signals holds practical significance for the prevention and treatment of hypertension and cardiovascular diseases. PVDF flexible pressure sensors possess the characteristics of high sensitivity, good flexibility, and strong biocompatibility, thereby demonstrating extensive application potential in areas such as health monitoring, wearable devices, and electronic skins. This paper focuses on the development of a modified piezoelectric polymer and its application in an intelligent blood pressure monitoring system, demonstrating its outstanding performance and feasibility through a series of experiments. This research provides innovative material choices for the development of intelligent medical devices and offers beneficial guidance for the design and application of future intelligent health monitoring systems.

Vapor and Light Responsive Biocompatible Soft Actuator.

Bioinspired smart polymeric materials that undergo three-dimensional shape deformation in response to specific stimuli have gained significant attention in the field of soft robotics and intelligent devices. Despite the substantial advancements in soft robotics, there is a growing demand for the design of multistimuli-responsive soft actuators using a single layer of material due to its reduced complexity and ease of manufacturing and durability. Here, we report the actuation characteristics of a single-layer, dual-responsive soft actuator that overcomes the commonly encountered delamination issues often associated with bilayer systems by incorporating PEDOT:PSS with cassava starch. This soft actuator exhibits deformations in response to various solvent vapors, such as water, alcohol, and acetone. Remarkably, it demonstrates opposite deformations upon exposure to water and alcohol vapors. Additionally, the actuator responds to light triggers and folds upon exposure to sunlight and infrared light. The degree of folding can be precisely controlled by adjusting the intensity of the light source. Furthermore, the periodic geometric patterns imposed on the surface of the actuator provide an additional handle to control the bending axis. For proof of concept, we leverage the actuation capabilities of our actuator to showcase a range of potential applications, including its usage in wearable textiles, crawler robots, smart curtains, push-and-pull machines, and smart lifts.

MXene-Based Soft Humidity-Driven Actuator with High Sensitivity and Fast Response.

Soft actuators possessing notable mechanical deformations, high sensitivity, and fast response speed play a crucial role in various applications, such as artificial muscles, soft robots, and intelligent devices. In this study, a smart humidity-driven actuator was successfully fabricated by utilizing MXene/cellulose nanofiber (CNF)/LiCl (MCL) through vacuum-assisted filtration with fast response speed and high sensitivity. Utilizing the excellent humidity responsiveness of MXene/CNF and the robust hygroscopicity of LiCl, the synergistic effect of these materials enhances the hygroscopic properties and response speed of the actuator. The MCL actuator demonstrates excellent actuation performance, fast deformation, and reliable cyclic stability. To illustrate the extensive potential of the soft actuator, a range of applications, from bionic devices to soft grippers and crawling actuators, are showcased. Remarkably, the crawling actuator demonstrates sustained crawling motion without necessitating a humidity switch, relying on the humidity gradient from water droplets, and exhibits spontaneous directional motions within a certain range, which makes it a promising prospect in the field of soft robotics.