IEEE Sensors Letters最新文献

{"title":"Ppb-Level Ammonia Sensing of Marigold Flower-Like NiO Nanostructure for Freshwater Fish Freshness","authors":"Bidesh Mahata;Pallab Banerji;Prasanta Kumar Guha","doi":"10.1109/LSENS.2024.3481308","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3481308","url":null,"abstract":"Fish freshness monitoring is now paramount for maintaining a healthy lifestyle. This letter represents the development of a marigold flower-like NiO nanostructure-based chemiresistor that can sense ppb-level ammonia for monitoring freshwater fish freshness. A simple low-temperature hydrothermal method was utilized to synthesize the sensing material. Using X-ray diffraction and a field emission scanning electron microscope, the synthesized material was examined in terms of structure and morphology. The sensor was fabricated using the drop casting method over gold interdigitated electrodes on alumina substrate. According to the gas sensing study, the sensor was more responsive to ammonia at 250 °C. The sensor device gained a response of 10% in the presence of 1 parts per million (ppm) ammonia. The response and recovery times were about 150 and 180 s, respectively, for 1 ppm ammonia. The experimental limit of detection of the sensor was 100 ppb. The proposed sensor is suitable for monitoring freshwater fish freshness.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142565542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KGAN-Based Semisupervised Domain Adapted Human Activity Recognition","authors":"Pritam Khan;Soham Chaudhuri;Dhruv Santosh Singh;Faisal Amaan","doi":"10.1109/LSENS.2024.3481149","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3481149","url":null,"abstract":"Human activity recognition (HAR) has become a popular stream in computing and wearable technologies, opening doors to multiple applications including healthcare and sports analysis. The primary challenge in HAR is developing models that generalize effectively across multiple domains due to variations in sensor qualities and individual differences. In addition, labeling the voluminous sensed data is a major challenge for classifying the activities. Therefore, domain adaptation approaches are being extensively investigated to help address these issues, transferring knowledge from a labeled source domain to a target domain. In this letter, a novel Kolmogorov–Arnold representation-based generative adversarial network (GAN), abbreviated as KGAN is designed for recognizing activities in a semi-supervised domain-adapted environment with enhanced robustness. The proposed KGAN-based HAR framework creates synthetic data for solving the scarcity of labeled data in the target domain and enables better handling of multidimensional data through structured function approximation. In addition, the combined use of kernel mean matching (KMM) and maximum mean and covariance discrepancy (MMCD) methods boosts the domain adapted framework by negating the weaknesses of each other. HAR experiments carried out on two publicly available datasets, namely, UCI-HAR and HHAR, exhibit enhanced performance of the proposed KGAN-based framework in target domain over few state-of-the-art models. The proposed framework significantly improves the overall accuracy of HAR across various domains by utilizing the strengths of GAN, KMM, and MMCD.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CDRA on Concave Conformal GP Loaded With Conformal FSS for Biomedical Applications","authors":"Manshree Mishra;Garima Tiwari;Pramod Kumar Gupta;Atul Kumar;Biswajeet Mukherjee","doi":"10.1109/LSENS.2024.3481258","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3481258","url":null,"abstract":"The development of a conformal frequency selective surface (FSS) loaded on a conformal cylindrical dielectric resonator antenna (CDRA) for the improvement of radiation characteristics for \u0000<italic>C</i>\u0000 band applications is presented in this letter. Sinusoidal slot aperture feeding is used for the excitation of the proposed structure. Perturbation on the CDRA is used to improve the impedance bandwidth of an antenna. For obtaining the circular polarization, CDRA is loaded with a conformal FSS at a distance of (2n ± 1) λ/4. To minimize radiation exposure to nearby human bodies, specific absorption rate (SAR) value is calculated, which is less than the 1.6 W/Kg, and the SAR value decreases as the distance between DRA and human head increases. The proposed structure is fabricated, and the measured results are in close agreement with simulated results.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TiO$_{2}$-Decorated MoS$_{2}$ Nanocomposite for CO$_{2}$ Sensing At Room Temperature","authors":"Rahul Gond;Prajjwal Shukla;Brajesh Rawat","doi":"10.1109/LSENS.2024.3480970","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3480970","url":null,"abstract":"Continuous and real-time monitoring of carbon dioxide (CO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000) has become an urgent demand due to its significant impact on climate change, asphyxiation risks, agricultural productivity, and human health. Electrochemical sensors for CO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000 monitoring face challenges, such as slow response time, high operating temperature, and lack of selectivity. To overcome these challenges, we propose a highly selective room-temperature (RT) CO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000 detection sensor based on TiO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000-MoS\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000 nanocomposite (NC), which is manufactured using a screen printing methodology. The fabricated sensor achieved a response of approximately 2.11% and response/recovery times of nearly 102/37s at 1000 ppm. The sensitivity is observed to be approximately 0.0032%/ppm with an excellent response for the CO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000 concentration range of 500–5000 ppm. Despite the typically low selectivity of unreactive CO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000 gas, the fabricated sensor exhibits high selectivity, with a response of around 2.21× higher than that of the CO gas with the next highest response. The scalable fabrication methodology and RT operation make TiO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000-MoS\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000 sensor a highly viable candidate for production through a cost-effective and high performance CO\u0000<inline-formula><tex-math>$_{2}$</tex-math></inline-formula>\u0000 sensing.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNA Sensing With Printed Circuit Board Electrode: Non-Faradaic Electrochemical Impedance Spectroscopy Analysis","authors":"Priyanka Roy;Avani Kulkarni;Siddharth Tallur","doi":"10.1109/LSENS.2024.3481057","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3481057","url":null,"abstract":"Printed circuit boards (PCBs) provide a versatile platform for developing point-of-use electrochemical biosensors. Low-cost surface finish, such as electroless nickel immersion gold, on such PCBs offers several advantages over traditional electrochemical sensor substrates, such as cost-effectiveness, scalability, miniaturization, and ease of fabrication. For DNA sensing application of these electrodes, it is necessary to understand the optimal parameter space for error-free operation. In this work, we aim to characterize the double-layer capacitance (DLC) formed at electrode/electrolyte interface for DNA sensing using PCB electrodes. This study investigates the electrochemical behavior of the DLC formed over PCB electrodes in phosphate-buffered saline (PBS) electrolyte using non-Faradaic electrochemical impedance spectroscopy. By varying the electrolyte concentrations (\u0000<inline-formula><tex-math>$text{1 mM}$</tex-math></inline-formula>\u0000, \u0000<inline-formula><tex-math>$text{5 mM}$</tex-math></inline-formula>\u0000, and \u0000<inline-formula><tex-math>$text{10 mM}$</tex-math></inline-formula>\u0000) and the ac excitation potential amplitudes (5-100 mV), we analyze DLC formation at the electrode/electrolyte interface. The study examines ionic arrangement transitions at the open circuit potential (OCP), and their impact on DLC retention and distortion. \u0000<inline-formula><tex-math>$text{5 mM}$</tex-math></inline-formula>\u0000 PBS electrolyte solution is found to best assist DLC formation as it has the highest capacitive contribution in impedance. In addition, the DLC formation is further examined with dilutions of \u0000<inline-formula><tex-math>$text{20 bp}$</tex-math></inline-formula>\u0000 DNA fragments prepared in 1 and \u0000<inline-formula><tex-math>$text{5 mM}$</tex-math></inline-formula>\u0000 PBS, ranging from \u0000<inline-formula><tex-math>$text{1 ng}/upmu text{l}$</tex-math></inline-formula>\u0000 to \u0000<inline-formula><tex-math>$text{20 ng}/upmu text{l}$</tex-math></inline-formula>\u0000 DNA. The dilutions prepared using \u0000<inline-formula><tex-math>$text{5 mM}$</tex-math></inline-formula>\u0000 PBS show sequential change in constant phase element (CPE) parameters of the impedance up to \u0000<inline-formula><tex-math>$text{10 ng}/upmu text{l}$</tex-math></inline-formula>\u0000 with OCP found to be maintained at a constant value of \u0000<inline-formula><tex-math>$text{40 mV}$</tex-math></inline-formula>\u0000. Higher DNA concentrations show decrease in OCP values, and thus this study presents optimal parameter space for DLC formation with proper ionic arrangement for accurate DNA detection using PCB electrodes.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ab-Initio Study on Vertical and Lateral Heterostructures of WS2–MoS2 for Gas Sensing","authors":"Pawan Kumar;Julaiba T. Mazumder;Ravindra K. Jha","doi":"10.1109/LSENS.2024.3480111","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3480111","url":null,"abstract":"The discovery of graphene has motivated research in the field of novel 2-D materials. A wide variety of 2-D materials with tunable electronic properties show promise in the development of gas sensors for their applications in medical devices and environmental monitoring. In this work, the first principle calculation based on density functional theory was carried out to study the adsorption of NO\u0000₂\u0000, NO, NH\u0000₃\u0000, CO, and H\u0000₂\u0000S on pristine WS\u0000₂\u0000 and its vertical and lateral heterostructures with MoS\u0000₂\u0000. The formation of heterostructures led to significant improvement in adsorption energy. Vertical heterostructures have shown the highest adsorption energy towards CO.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Throughput Antimicrobial Susceptibility Assessment Using Non- Faradaic Electrochemical Impedance Spectroscopy","authors":"Rhea Patel;Surya Varchasvi Devaraj;Hasika Suresh;Kundan Saha;Maryam Shojaei Baghini;Sameer Sonkusale","doi":"10.1109/LSENS.2024.3480121","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3480121","url":null,"abstract":"In this letter, we present a label-free antimicrobial susceptibility test using non-Faradaic electrochemical impedance spectroscopy (nF-EIS) as a viable method to rapidly quantify antibiotic resistance. Different antibiotic resistant strains of \u0000<italic>Shewanella oneidensis</i>\u0000 were used as a model bacteria to measure minimum inhibitory concentration of antibiotic, namely, kanamaycin needed to kill sufficient microbes. The device consists of gold interdigitated electrodes on polyethylene terephthalate substrate that can process 50 µL volume in less than 10 min. After incubating the bacteria with kanamycin for 10 min, roughly 106 cells are analyzed using impedance spectroscopy. The observed Bode magnitude and phase plots for different strains of \u0000<italic>S. oneidensis</i>\u0000 reflect the antibiotic action on the strains and its minimum concentration requirement for its effect is determined and the data are further used to develop an equivalent electrical model to quantify the susceptibility.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 12","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-Complexity Attention-Based Unsupervised Anomalous Sound Detection Exploiting Separable Convolutions and Angular Loss","authors":"Michael Neri;Marco Carli","doi":"10.1109/LSENS.2024.3480450","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3480450","url":null,"abstract":"In this letter, a novel deep neural network, designed to enhance the efficiency and effectiveness of unsupervised sound anomaly detection, is presented. The proposed model exploits an attention module and separable convolutions to identify salient time–frequency patterns in audio data to discriminate between normal and anomalous sounds with reduced computational complexity. The approach is validated through extensive experiments using the Task 2 dataset of the DCASE 2020 challenge. Results demonstrate superior performance in terms of anomaly detection accuracy while having fewer parameters than state-of-the-art methods.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10716469","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image-Based Analysis Method for Detecting a Rebar in Concrete Using Short-Time Fourier Transform (STFT)","authors":"Shinyeon Kim;Minjeong Kim;Moon-Jung Kwak;Heejin Hwang;Seunghyun Song;Youngjun Joo","doi":"10.1109/LSENS.2024.3479408","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3479408","url":null,"abstract":"The appropriate location of reinforced structures is critical for building stability. However, due to the shortage of well-trained labor and lack of management and supervision, poor construction and collapse accidents in the concrete structure are increasing. In this letter, we conduct nondestructive testing (NDT) with ultrasonic signals to determine the presence of a rebar within the concrete block. The experiments are performed at two distinct locations with and without a rebar. Subsequently, the short-time Fourier transform (STFT) is performed on the data from each location, and the resulting images are plotted to identify features. It is observed that the frequency bands vary depending on the presence of a rebar. It allows us to extract distinguishable features in STFT images based on the presence of the rebar. To validate the effectiveness of obtained features, image classification using Python codes is conducted, demonstrating high accuracy. Therefore, STFT images enable the determination of the presence of the rebar within the concrete structure.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 11","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Detection of Spot Jamming Attacks in mmWave Radar Systems Using a Lightweight CNN","authors":"Vamsi Krishna Puduru;Rakesh Reddy Yakkati;Bethi Pardhasaradhi;Korra Sathya Babu;Linga Reddy Cenkeramaddi","doi":"10.1109/LSENS.2024.3480815","DOIUrl":"https://doi.org/10.1109/LSENS.2024.3480815","url":null,"abstract":"Millimeter-wave (mmWave) radars are integral to advanced driver assistance systems for object detection and tracking. However, these radars are vulnerable to interference from other mmWave radars in the vicinity, potentially leading to false detections and tracking errors. This letter focuses on identifying which frames of ego radar data are affected by spurious signals from a spot jamming attack (a scenario where one radar intentionally interferes with another with the same specifications). We conducted experiments using two AWR1843 radars, with one acting as the jammer, and observed only a few frames of data were falling under a spot jamming attack. We transformed the in-phase and quadrature-phase (I-Q) data from the ego radar into range-angle heatmap images using 2-D fast Fourier transform (2D-FFT). On 2D-FFT images, a lightweight convolution neural network (CNN) classifier with a model size of 5MB is proposed to distinguish between jammed and nonjammed frames. The classifier exhibits a 95.4% accuracy in ten-fold cross-validation, outperforming pretrained models, such as DenseNet, EfficientNet, InceptionNet, MobileNet, NASNet, ResNet, VGGNet, ConvNeXt, and Xception. Moreover, the CNN was successfully deployed on edge devices, Raspberry Pi, and other processors, observing the execution of CNN in just 15.8 milliseconds per frame. This work demonstrates the potential for real-time detection of spot jamming attacks, with applications in electronic counter-countermeasures, source localization, machine learning (ML)-aided passive radar systems, and cognitive radar development.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 12","pages":"1-4"},"PeriodicalIF":2.2,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}