2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)最新文献_第4页

Detection of Malicious Traffic in IoMT Environment Using Intelligent XGboost Approach 基于智能XGboost的IoMT环境恶意流量检测

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10113978

Yugandhar Manchala, Janmenjoy Nayak, H. Behera

{"title":"Detection of Malicious Traffic in IoMT Environment Using Intelligent XGboost Approach","authors":"Yugandhar Manchala, Janmenjoy Nayak, H. Behera","doi":"10.1109/OTCON56053.2023.10113978","DOIUrl":"https://doi.org/10.1109/OTCON56053.2023.10113978","url":null,"abstract":"The paradigm of computing has completely altered as a result of the development of communication and Information technology. The Internet of Things (IoT) is a type of communication environment made up of web-enabled devices that can communicate, gather, assess, and send data across the network without the need for human participation. The IoT idea is widely established in numerous fields of application, and it has also been used in the medical industry. The Internet of Medical Things (IoMT) refers to the combination of IoT with medical technology. Even though IoMT applications have facilitated real time monitoring in the healthcare sector, it suffers from several security and privacy attacks. The presence of such security and privacy attacks can cause the alteration or disclosure of sensitive data or sometimes authorized users cannot access the data also. Hence, it is crucial to secure the IoMT environment from such malicious attacks. Therefore, this study aims in assessing harmful traffic in IoMT environment. In this research, XGBoost classification algorithm is proposed to classify malicious traffic in an IoMT environment. Further, the study has also implemented state-of-art machine learning algorithms such as DT (Decision Tree), RF (Random Forest), LR (Logistic Regression), SVM (Support Vector Machine), NB (Naive Bayes), MLP (Multilayer Perceptron), SGD (Stochastic Gradient Descent) to test the efficacy of the proposed model. The experimental outcomes indicate that the proposed XGBoost algorithm outperformed other conventional machine learning approaches in terms of predicting malicious traffic in an IoMT environment, with a 100-percentage accuracy rate. Furthermore, the XGBoost algorithm exhibits better performance in terms of precision, Fl-score, recall, and AUC as compared with traditional approaches.","PeriodicalId":265966,"journal":{"name":"2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132820210","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}

引用次数: 0

Recent Trends in Remote Healthcare Applications and Futuristic Approach 远程医疗应用的最新趋势和未来方法

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10113949

Smita Wagholikar, Omkar Wagholikar

引用次数: 0

Automatic Bottle Filling and Capping Machine using SCADA with the Internet of Things 采用SCADA和物联网的自动灌装旋盖机

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10114011

B. Prasanna, G. MadhusudhanaRao, Shashikant Kaushaley, Srinivas Nakka, P. K. Jena

{"title":"Automatic Bottle Filling and Capping Machine using SCADA with the Internet of Things","authors":"B. Prasanna, G. MadhusudhanaRao, Shashikant Kaushaley, Srinivas Nakka, P. K. Jena","doi":"10.1109/OTCON56053.2023.10114011","DOIUrl":"https://doi.org/10.1109/OTCON56053.2023.10114011","url":null,"abstract":"In today’s fast-paced, fiercely competitive industrial environment, a business must be adaptable, efficient, and well-organized if it hopes to survive. Streamlining operations in speed, dependability, and product output has led to a significant need for industrial control systems and automation in the process and manufacturing industries. As a result, automation’s impact on daily life and the global economy is growing. This study aimed to develop an IoT-based SCADA for an automatic bottle-filling and capping system. The WinCC Explorer software used to design the production contour and monitor and control it is intended for use in this simulation. Delta was used to develop and test the ladder diagram. To reduce the number of rejected bottles, the system was designed to utilize a retentive timer instead of an on/off delay timer. The system’s primary characteristics included low power consumption, low operating costs, minor maintenance, and less fluid loss. All of these factors ultimately improved costeffectiveness and raised the profit margin. Fully automated bottling facility that achieves vital energy and efficiency savings through speed control. It is advised to employ a completely automated system rather than a traditional control system in light of the findings and recommendations.","PeriodicalId":265966,"journal":{"name":"2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133032002","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}

引用次数: 2

Deep-learning models for Covid-19 Detection Using Chest X-Ray Images 利用胸部x射线图像检测Covid-19的深度学习模型

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10113965

Prabhakar Semwal, R. Saini

{"title":"Deep-learning models for Covid-19 Detection Using Chest X-Ray Images","authors":"Prabhakar Semwal, R. Saini","doi":"10.1109/OTCON56053.2023.10113965","DOIUrl":"https://doi.org/10.1109/OTCON56053.2023.10113965","url":null,"abstract":"Deep Convolutional Neural Networks are a form of neural network that can categorize, recognize, or separate images. The problem of COVID-19 detection has become the world’s most complex challenge since 2019. In this research work, Chest X-Ray images are used to detect patients’ Covid Positive or Negative with the help of pre-trained models: VGG16, InceptionV3, ResNet50, and InceptionResNetV2. In this paper, 821 samples are used for training, 186 samples for validation, and 184 samples are used for testing. Hybrid model InceptionResNetV2 has achieved overall maximum accuracy of 94.56% with a Recall value of 96% for normal CXR images, and a precision of 95.12% for Covid Positive images. The lowest accuracy was achieved by the ResNet50 model of 92.93% on the testing dataset, and a Recall of 93.93% was achieved for the normal images. Throughout the implementation process, it was discovered that factors like epoch had a considerable impact on the model’s accuracy. Consequently, it is advised that the model be trained with a sufficient number of epochs to provide reliable classification results. The study’s findings suggest that deep learning models have an excellent potential for correctly identifying the covid positive or covid negative using CXR images.","PeriodicalId":265966,"journal":{"name":"2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115408987","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}

引用次数: 0

Student Location Reporting System Using Arduino Uno 基于Arduino Uno的学生位置报告系统

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10113991

N. Gaddam, R. Rao

引用次数: 0

Real Time Object Detection for Assisting Visually Impaired People 帮助视障人士的实时目标检测

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10114050

Kashish Sharma, P. Syal

{"title":"Real Time Object Detection for Assisting Visually Impaired People","authors":"Kashish Sharma, P. Syal","doi":"10.1109/OTCON56053.2023.10114050","DOIUrl":"https://doi.org/10.1109/OTCON56053.2023.10114050","url":null,"abstract":"Visually impaired people struggle with several issues in their daily lives, especially when they visit new places. It is difficult for them to move anywhere without guidance, making them dependent on someone. Nowadays, with the development of technology, some automated approaches have been designed to assist them, but still, there is a scope for improvement. The main driving force behind this work was to design and construct an object detector that can help visually impaired people by detecting objects in real-time. So, the main aim of this work is to develop a system for real-time object detection based on deep learning. Several models were developed earlier with different aims; many were used for object detection. In this work, an improved model of YOLOv5 is proposed where coupled head is replaced with an enhanced decoupled head, also improved loss and activation functions are used. Moreover, text-to-speech conversion library of google is also used for conversion of detected class of the object into an audio signal to provide information to visually impaired people. Finally, the experimentation was done using a model trained with the COCO dataset and tested using a COCO test set and a webcam. The results deliberate the effectiveness of the improved YOLOv5 compared to conventional YOLOv5 by calculating precision and recall.","PeriodicalId":265966,"journal":{"name":"2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123341553","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}

引用次数: 0

Digital Payments Revolution: A Study of Awareness, Acceptance, and Usage of Unified Payments Interface Technology Among Selected Women in India 数字支付革命:印度特定女性对统一支付接口技术的认识、接受和使用的研究

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10114004

Jalpa Thakkar, Prerak Thakkar

{"title":"Digital Payments Revolution: A Study of Awareness, Acceptance, and Usage of Unified Payments Interface Technology Among Selected Women in India","authors":"Jalpa Thakkar, Prerak Thakkar","doi":"10.1109/OTCON56053.2023.10114004","DOIUrl":"https://doi.org/10.1109/OTCON56053.2023.10114004","url":null,"abstract":"Unified Payments Interface (UPI) has turned out to be a game-changer in the Indian economy in digital payments ecosystems over a period of time. From a small vegetable vendor to a rich businessman, all have started adopting UPI technology in India. The change in trend from cash to digital payments has been very interesting from 2016 onwards. This paper reviews the different initiatives strategized by the Indian government which led to the increased usage of UPI. The current research study focuses on awareness, acceptance, and usage of UPI among selected women in Pune region. The study includes descriptive statistics, exploratory data analysis, and hypotheses testing. The data is analyzed using Python statistics libraries. Research shows that the majority of the women respondents have installed UPI on their own mobile but they still tend to prefer cash transactions over UPI in day-to-day life. Interestingly, women below the age of 40 prefer UPI transactions over cash. Occupation of a woman does not affect the preference for UPI or cash as a mode of transaction. The study also indicates that the age and occupation of women have an impact on the awareness about the knowledge of UPI and its configuration.","PeriodicalId":265966,"journal":{"name":"2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124008020","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}

引用次数: 0

ARIMA time Series Model vs. K-Means Clustering for Cloud Workloads Performance ARIMA时间序列模型与K-Means聚类对云工作负载性能的影响

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10113979

V. Mishra, Megha Mishra, Sunil Tekale, T. N. Praveena, Rachakonda Venkatesh, B. Dewangan

{"title":"ARIMA time Series Model vs. K-Means Clustering for Cloud Workloads Performance","authors":"V. Mishra, Megha Mishra, Sunil Tekale, T. N. Praveena, Rachakonda Venkatesh, B. Dewangan","doi":"10.1109/OTCON56053.2023.10113979","DOIUrl":"https://doi.org/10.1109/OTCON56053.2023.10113979","url":null,"abstract":"To develop a thriving ability plan and protect the observable of Internet service providers of cloud environment, the increased heterogeneity brought on by various Cloud workloads, such as Business Data analytics, Big Data, IoT and calls for exact sensors. Although K-Means is an easy and quick clustering technique, it might not fully account for the heterogeneity present in Cloud platform workloads. The Multiple patterns can be found using ARIMA time series Models, which is trained for data prediction on cloud be combined into cohesive, homogenous components that closely resemble the data set’s actual patterns. In order to assess the cluster suggest the two different approaches for heterogeneity in resource utilization of Cloud infrastructure, this study compares ARIMA time series Model and K- Means. Clusters generated using K-Means yield significantly abstracted information, according to Bitbrains’ experiments using Google cluster trace and business-critical workloads. A more accurate clustering with discrete usage boundaries is provided by the ARIMA time series Model. Even though the ARIMA time series Model takes longer to compute than K-Means, it can be employed when a finer-grained characterization and study of the workload is needed.","PeriodicalId":265966,"journal":{"name":"2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720687","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}

引用次数: 0

Hybrid Image Captioning Model 混合图像字幕模型

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10113957

Lipismita Panigrahi, Raghab Ranjan Panigrahi, S. K. Chandra

{"title":"Hybrid Image Captioning Model","authors":"Lipismita Panigrahi, Raghab Ranjan Panigrahi, S. K. Chandra","doi":"10.1109/OTCON56053.2023.10113957","DOIUrl":"https://doi.org/10.1109/OTCON56053.2023.10113957","url":null,"abstract":"Image captioning is implemented using Deep learning and NLP (Natural Language Processing) resulting in producing a description of an image. The proposed model generates a caption for an image using a Convolutional Neural Network (CNN) together with a Recurrent Neural Network (RNN) and area of attention. Previously, the image names were used as keys to map the images with descriptions. In order to achieve high performance, in the proposed model the image caption is based on the relationship between the areas of a picture (attention model), the words used in the caption, and the state of an RNN language model. The approach of progressive loading is employed for the loading of the image dataset. Further, for encoding the image dataset into a feature vector, VGG16 a pre-trained CNN is used. The extracted feature vector is given as input to the RNN model. These image encodings are output to a specific type of RNN model known as Long Short-Term Memory (LSTM) networks. Subsequently, the LSTM works on decoding the feature vector and predicts the sequence of words, resulting in the generation of descriptions or captions. The training performance is measured using one of the model’s quantitative analysis metrics known as BLEU.","PeriodicalId":265966,"journal":{"name":"2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122379951","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}

引用次数: 0

TBSMFA: Trust-Based Security Mechanism for SYN Flooding Attack at Transport Layer using DRICC technique in WSN 基于信任的WSN传输层SYN泛洪攻击安全机制

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON) Pub Date : 2023-02-08 DOI: 10.1109/OTCON56053.2023.10113952

Umashankar Ghugar, Gv Sivanarayan, Gnv Rajareddy, K. Varma, G. Lakshmeeswari

引用次数: 0