2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)最新文献

{"title":"Blockchain enabled vehicular networks: a review","authors":"R. Tandon, Ajay Verma, P. K. Gupta","doi":"10.1109/IMPACT55510.2022.10029136","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029136","url":null,"abstract":"Vehicular network is an emerging and advanced component in the field of transportation systems. In vehicular network, all authenticated vehicles can communicate with each other and with other components of the network. This is done to ensure the security of the information shared among vehicles. The information may contain sensitive data like speed of vehicle, vehicle's identity, and current position of vehicle. Vehicular network provides various different advantages to drivers but at the time it is susceptible to privacy and security attacks. It is essential to address various security and privacy issues. Existing possible solutions are not feasible for providing security in the vehicular network. Therefore, blockchain has been introduced in the vehicular network that provides decentralized platform which is capable of managing and handling resources. Further, it resists various security attacks that may occur in the network. This paper provides the review of blockchain-based vehicular network and discusses the various schemes used by different authors involving blockchain in vehicular networks.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126219663","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":"Ensemble model for ECG Classification","authors":"Abdul Haque, N. Akhtar","doi":"10.1109/IMPACT55510.2022.10029230","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029230","url":null,"abstract":"Electrocardiography (ECG) is a relatively popular diagnostic technique that does not involve any kind of bodily invasion, and algorithms are increasingly supporting its interpretation. There has been a shortage of relevant datasets for training in this area of work and there will be lack of clearly defined evaluation procedure, which has slowed progress in the field of automated analysis of electrocardiograms (ECGs). These factors have made it difficult to compare the effectiveness of various algorithms. PTB-XL is a clinical 12-lead electrocardiogram dataset that was just released and is easily available. Here, we illustrate a range of results for this dataset., which covers a classification job based on a variety of ECG statements. This is done so that we may get around the issues that have been brought up. Among the deep learning-based time series classification approaches that were researched and examined, convolutional neural networks, and especially vgg16 and alexnet-based architectures, provide the greatest performance. The vgg16-based convolutional method achieves 0.8710 accuracy and 0.9448 AUC when applied to the ECG dataset. The ensemble model achieves the accuracy of 0.8690 and AUC of 0.9431. In the PTB-XL dataset, we used a 100 Hz sample rate for our training purposes. We split out the PTB-XL dataset into training, which is approx. 70% of the data, testing, which occupies 15% of the dataset, and the remaining 15% is for the validation set. The findings demonstrate that the strategy presented here is not only effective but also accurate when it comes to classifying ECG signals.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126064477","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":"Classification of Bearing Faults using Discrete Wavelet Packet Analysis and Support Vector Machine","authors":"Afroz Ahmed Saad, Sidra Khanam","doi":"10.1109/IMPACT55510.2022.10029049","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029049","url":null,"abstract":"The automation of condition monitoring strategies of industrial sectors is on the rise with the current industrial revolution. The automatic detection and classification of bearing faults using machine learning is also one of the application domains. A lot has been investigated into the use of different classifiers for bearing fault classification and of them, Support Vector Machine (SVM) has emerged out as a simple and confident classifier. Sufficient studies are available on selecting the features from raw vibration data and then training them using SVM; however, there is a dearth in investing the role of denoised signal for feature extraction. This work presents a comparative study of extracting the features from raw signal and signal processed through Discrete Wavelet Packet Analysis (DWPA). For this the opensource data from Case Western Reserve University has been used and the compressed and denoised signals are obtained using Symlet5 wavelet. The features obtained from raw, compressed and denoised signals are trained using different SVM classifier and their classification accuracies are compared. The classification accuracy is enhanced by using the denoised signal for fault investigation.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122224727","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":"Assistive Stick for Visually Impaired People","authors":"Danish Khan, M. Zamir, M. S. Umar, Zafaryab Haider","doi":"10.1109/IMPACT55510.2022.10029287","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029287","url":null,"abstract":"Blind or visually impaired people have difficulty navigating the street and are also unaware of nearby landmarks. They need an assistant (e.g. a cane, human, dog, e.t.c.) to go from one place to another place. In this modern era, it is possible to develop smart solutions with the help of modern technologies like deep learning (DL), natural language processing (NLP), internet of things (IoT), etc. that can assist them without any human intervention. A smart stick is one of the solutions that can help them with navigation and get to know the surrounding places. This paper proposed a smart solution and developed a smart stick to help visually impaired people with the use of DL and NLP and devices like the Raspberry Pi, an ultrasonic sensor, and a camera. This smart stick can detect obstacles using an ultrasonic sensor within the range of 1.5 metres and alert the person by generating audio as a warning message. The stick is also able to capture images from its surroundings using the camera and can read the text present in the captured image. The text in the image is detected using a deep learning model called the EAST text detector and recognised using an OCR Engine tesseract. Furthermore, the recognised text is converted into audio so that the person can hear about their surroundings. All calculations and processing are done on the Raspberry Pi, and the generated audio can be heard by using a speaker(earphone or headphone). The proposed solution is successfully implemented and demonstrated, and it is found to be very efficient and cost-effective.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123209238","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":"IOT Based Smart Agriculture Using LIFI","authors":"A. Vijayakrishna, G. G, Mohd Dilshad Ansari, G. Suryanarayana","doi":"10.1109/IMPACT55510.2022.10029255","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029255","url":null,"abstract":"Modernization of the conventional farming procedure is one of the major concerns for a nation like India that needs to import agro items from various nations to cater to the needs of around 1.2 billion people. One of the main challenges of agriculture is that most of the conventional methods of agriculture are majorly manual which is still prevalent among the farmers. These results in unnecessary usage of pesticides and wastage of water in irrigating fields when not required. The proposed work is an IoT Based Smart Agriculture system using Light Fidelity (LiFi) that is fully automated and checks the farm field using IoT. Besides uncommon instruments, web related things or gadgets, things inserted with devices, sensors, programming forms Internet of Things (IoT) which is a key part of future web. The framework consists of sensors that are deployed in the field and they sense parameters like temperature, light and soil moisture and then data is analyzed by Micro Controller Unit (MCU). The data is then transferred to the receiver end through LiFi transmitter. The system has been developed by using PIC microcontroller as it is very convenient to use. LiFi offers more security over Wi-Fi or any wired connection and is faster hence the integrity of the agricultural data can be secured while transmitting for analysis. LiFi is eco- friendly too. Through IoT farmer can access the information from anywhere at any time. Automated monitoring of field parameters helps in producing high quality yield.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131851295","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":"Physical Insight into electrostatically doped TFET considering Ambipolarity conduction","authors":"Nazia Haneef, MD. Yasir Bashir, M. A. Raushan, M. J. Siddiqui","doi":"10.1109/IMPACT55510.2022.10029325","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029325","url":null,"abstract":"To substitute physical doping or acceptor dopant species with free electron or hole charges generated by electrodes, electrostatic doping is one of the emerging strategies in device design. Due to this, we examined the conventional Tunnel Field Effect Transistor (TFET) based on electrostatic doping in this study, known as the electrostatically doped TFET (ED-TFET). Our investigation concentrated mostly on ambipolar leakage current, one of the inherent issues with TFETs. Additionally, we suggest using drain oxide thickness (PG1-OT) to greatly reduce ambipolarity conduction. Finally, we have examined the performance of the suggested structure on analog characteristics like transconductance (gm) and cutoff frequency (fT) and we have also examined the impact of PG1-OT electrode length on the proposed device.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120950868","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":"Bulk heterojunction PTB7-Th: ICBA-based Optoelectronic Devices","authors":"Minakshi Sharma, C. Negi, P. A. Alvi, S. Gupta","doi":"10.1109/IMPACT55510.2022.10029022","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029022","url":null,"abstract":"Here, we have prepared the bulk heterojunction (BHJ) of Poly([2,6-4,8-di(5-ethylethexylthienyl)benzo[1,2-b;3,3-b]dithiophene]{3-fluro-2[(2-ethylhexyl)carbonyl]thieno[3,4b]thiophenediyl (PTB7-Th):Indene-C60 Bisadduct (ICBA) based composites to study the optoelectronic properties and utilize it in the photoactive layer of optoelectronic devices. The solution processing method has been used to prepare the composite thin film. Field emission scanning electron microscopy analysis validates the development of the composite of donor and acceptor polymers. The as-prepared composites were used to fabricate the device, having the photoactive layer made by composites PTB7-Th: ICBA. The enhanced absorption region was obtained in the UV-Visible spectra of the composite. The device demonstrated greater optoelectronic performance in the illumination condition. Higher interface quality may be ascribed to better optoelectronic performance since the ideality factor of the composite obtained in the dark is smaller than that achieved under illumination.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116455789","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":"Intelligent Prediction of Multiple Defects in Rolling Element Bearing using ANN Algorithm","authors":"Md Asif Ali Khan, M. Jamil, Sidra Khanam","doi":"10.1109/IMPACT55510.2022.10029154","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029154","url":null,"abstract":"Rolling Element Bearing (REB) failure in heavy rotating machines or assembly lines might cause the machine to shut down, affecting the total cost and quality of the product. Bearing condition monitoring prevents failure and reduces the time and expense of preventative maintenance. With the advent of machine learning in the area of condition monitoring of mechanical systems, Artificial Neural Network (ANN) is becoming more widely used, redefining the state-of-the-art in defect diagnosis and classification. This work provides a real-time online fault detection approach for rolling bearings based on the ANN algorithm in order to realize the predictive maintenance of rolling element bearings in the industry. The training of the fault diagnostic model and the real-time fault diagnosis are the two primary steps of the procedure. The vibration signal is first preprocessed, which includes data categorization, data segmentation, and feature extraction before the defect diagnosis model is trained and optimized. The extraction of the characteristic features of the vibration signal is utilized to implement the online fault diagnosis through the fault diagnostic model. The fault data for analysis is accessed from the open-source Paderborn university bearing data. The fault categories taken are of multiple faults on the inner and the outer raceways. Optimization is carried out in the ANN model with regard to its number of hidden layers, size of the layers and the activation function to seek for a set of these parameters, which result in the best performance in diagnosing the bearing defects for the fault categories under consideration. The ANN approach is proved to be a useful technique for detecting faults and improving classification accuracy, making it more suitable for rolling bearing fault diagnosis. A maximum fault classification accuracy of 98.5% was achieved with a single hidden layer of size 25 and the Tanh activation function. The corresponding training time was 3.9831 seconds, and the prediction speed was found to be 24000 observations per second.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114153495","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":"Fourier Analysis Based Respiration Rate Estimation Using Corrupted Photoplethysmogram Signal","authors":"Pankaj, Ashish Kumar, R. Komaragiri, Manjeet Kumar","doi":"10.1109/IMPACT55510.2022.10029065","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029065","url":null,"abstract":"This work proposes a Fourier series-based Fourier decomposition method (FDM) technique to analyze the photoplethysmography (PPG) signals to estimate respiration rate (RR). The proposed method consists of data acquisition, preprocessing, signal decomposition into Fourier intrinsic band function (FIBFs), Superposition of clean FIBFs, fast Fourier transform, spectral peak identification, and estimation of RR. The efficacy of the proposed FDM-based RR estimation method is evaluated using the CapnoBase database, a benchmark RR estimation database. The proposed method improves estimation accuracy with a mean absolute error (MAE) value of 1.02 breaths per minute (BPM) and a root mean square error value (RMSE) of 1.22. The proposed method can accurately estimate vital physiological parameter RR from the PPG signal.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116741152","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":"On T-Spherical Fuzzy Hypersoft Sets and Their Aggregation Operators with Application in Soft Computing","authors":"Pranjal Bansal, Himanshu Dhumras, R. Bajaj","doi":"10.1109/IMPACT55510.2022.10029247","DOIUrl":"https://doi.org/10.1109/IMPACT55510.2022.10029247","url":null,"abstract":"In the decision sciences problems, systematic evaluation of information containing incompleteness and impreciseness having the feature of parametrization is one of the substantial features. In the present communication, a new notion of T-spherical fuzzy hypersoft set (TSFHSS) has been introduced which contains an additional capacity of accommodating the components of neutral membership (abstain) and refusal compared to intuitionistic fuzzy hypersoft set under the sub-parametrization in an exponential way. Some of the basic operations on T-spherical fuzzy hypersoft set and some important aggregation operators have been presented and studied in detail. Further, in order to exhibit an application in the field of soft computing, the selection problem of COVID-19 mask has been numerically illustrated with some advantageous and concluding remarks.","PeriodicalId":300301,"journal":{"name":"2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT)","volume":"4 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130076298","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}