S. Asif, T. Anil, Satwik Tangudu, GH Sai Keertan, D. S.
{"title":"Traffic Sign Detection Using SSD Mobilenet & Faster RCNN","authors":"S. Asif, T. Anil, Satwik Tangudu, GH Sai Keertan, D. S.","doi":"10.1109/ViTECoN58111.2023.10157917","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157917","url":null,"abstract":"This paper presents a deep learning-based approach to traffic sign detection. The proposed approach utilizes state- of-the-art object detection models, such as SSD and RCNN, to detect traffic signs in real time. Tensorflow is used as a platform for training deep learning models and the models are being implemented on Google Colab and Kaggle cloud due to the GPU availability on the respective platforms. The models are evaluated on a traffic sign dataset from Kaggle, and it achieves high detection accuracy. Moreover, the proposed approach is robust to different lighting and weather conditions and is capable of detecting traffic signs from various distances and angles. The findings of this study show that by effectively detecting and recognizing traffic signs, deep learning-based techniques can potentially increase the safety and effectiveness of transportation networks.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121345995","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":"An Efficient Node to Node Coverage and Connectivity with RSSI Using Grey-Wolf Prediction Optimization Algorithm in Remote Low Accessibility Area","authors":"Sean Laurel Rex Bashyam, Jyotsna Chandra, R. S","doi":"10.1109/ViTECoN58111.2023.10157547","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157547","url":null,"abstract":"Wireless Sensor Networks (WSN) which are specifically designed for monitoring disaster applications require precise knowledge of the location of the sensor nodes, since the nodes tend to relocate from their initial deployed position when disaster strikes. In addition, due to sensing, processing and transmission of monitored data, energy of the nodes gets depleted resulting in energy holes and might lead to partition in the network which is undesirable. In this work, Delaunay Triangulation (DT) method is used to determine the Point of Intersection (POI) between the partitioned sensor node groups. Received Signal Strength Indicator (RSSI) and Predicted Received Signal Strength Indicator (PRSSI) techniques are used to find the connectivity strength between the partitioned group nodes and the POI. Grey Wolf Optimization with Weight Prediction Algorithm (GWO-WP) is used to improve RSSI and arrive at a stronger POI. It is also shown that the use of mobile nodes to collect data from multiple POI establishes good connectivity between the partitioned groups.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123292102","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":"SEEMA: An Automation Framework for Vulnerability Assessement and Penetration Testing","authors":"Yash Tyagi, Shubham Shekhar, A. P, S. Bhardwaj","doi":"10.1109/ViTECoN58111.2023.10157032","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157032","url":null,"abstract":"The world has witnessed an exponential increase in the number of Internet Connected Computers due to various causes. This exponential increase and the resulting dependence have had far reaching cybersecurity implications. The primary implication being exponential rise in cybercrime which necessitates the vulnerability assessment and penetration testing (VAPT). The vulnerability assessment and penetration testing aids in offsetting any liability associated with a successful attack on an organization's asset. The current frameworks and tool available for VAPT require very high expert knowledge and are predominantly manual. Moreover, some tools available automate only certain phases of VAPT but not the whole process. This mismatch provides the opportunity to create a solution by automating the whole process while lowering the knowledge threshold. Thus, this paper provides a revamped automated framework for a novice individual and a cybersecurity professional's use. It also provides a framework for commercial use which leverages multi-agent system and certain aspects of full stack monitoring.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"140 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129048693","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}
K. Srilatha, D. Rushikeshwar, N.R Bhaskar Chowdary
{"title":"Smart Warehouse Monitoring System using Internet of Things (IoT)","authors":"K. Srilatha, D. Rushikeshwar, N.R Bhaskar Chowdary","doi":"10.1109/ViTECoN58111.2023.10157621","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157621","url":null,"abstract":"The Internet of Things (IoT) technology is used in smart warehousing, a monitoring system. Crops are stored and preserved in some ideal state after harvest. IoT sensors gather information on the warehouse climate and take prompt action in response to the farmers' input. Using Arduino and sensors, this system gives farmers access to real-time information about their products or goods. Fruits and vegetables can be kept fresh for longer by using proper air conditioning. In this approach, crop preservation is achieved by smart warehousing, which controls warehouse variables like temperature and humidity while retaining ambient conditions and room climate. Also, our sensors let us know if any thefts are occurring in our warehouse.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130452928","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}
Soumyalatha Naveen, Nayana Anil, Prerana M, Shalen Janet S, Yashasvi V
{"title":"Analysis of Blood Pressure using Data Mining Techniques","authors":"Soumyalatha Naveen, Nayana Anil, Prerana M, Shalen Janet S, Yashasvi V","doi":"10.1109/ViTECoN58111.2023.10157138","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157138","url":null,"abstract":"Hypertension is a serious public health concern. Diseases related to high blood pressure (BP) such as cardiovascular disease (CVDs) have emerged as one of the main dangers to human health. Cardiovascular disease caused due to hypertension is a widespread chronic disease. Monitoring blood pressure (BP), a physiological indication for cardiovascular systems is a useful strategy for preventing CVDs. An intervention that helps in the early management and prevention of hypertension is risk prediction. Effective incident prevention has been shown to need continuous BP measurement. The use of non-intrusive blood pressure monitoring in continuous measurement appears promising in contrast to conventional prediction models that have poor measurement accuracy or require extensive training. As a result, linear regression is suggested and used to address the issue in this study. The goal is to build predictive models, such as linear regression - a machine learning technique that can identify people at a high risk of developing hypertension without invasive clinical procedures. With the help of one or more independent variables, a dependent variable is predicted using the Modelling technique of linear regression. In this article, blood pressure is analyzed by considering age, weight, stress, and pulse.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130627527","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":"A High-Gain and Dual-band MSPA 1x2 array for 5G n78/n79 Sub-6GHz Cellular applications","authors":"Idrish Shaik, Krishna Veni Sahukara","doi":"10.1109/ViTECoN58111.2023.10157642","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157642","url":null,"abstract":"In this article, the simulation and design of the simple 1×2 MSPA array was designed for use in the 5G mid bands n78/n79 are provided with L-Slots on left and right side of patch elements with dimensions of 35×52×1.5mm3. The RT Duriod/Rogers 5870(εr =2.33) was used to manufacture this antenna model and it was designed by using CST Studio suite 2019 EM solver. The L slot cut 1×2 array gives radiation efficiency of 91 % and 82% resonating at 3.448GHz and 4.728 GHz with maximum gains of 9.56dBi and 6.88dBi and also the realized gain is 8.93dBi and 6.1 dBi. Because of high gain and maximum radiation efficiency, this model can be used in broadband applications of C-band n78 and n79 5G mid bands which consist of narrow channel bandwidth.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124489237","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-Performance Authentication and Efficient Block Creation: Ethereum","authors":"Deepika Kamboj, Minakshi Chauhan, K. K. Gola","doi":"10.1109/ViTECoN58111.2023.10157457","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157457","url":null,"abstract":"At present, there is rapid growth in storing data online. Online data storage enables users to access their information anywhere and anytime. However, this can lead to some security issues, which can be handled today using Blockchain. Numerous researchers have worked on various blockchain application domains, including supply chain management, the medical industry, governance, etc. In addition to these applications, many issues still need research, such as security, privacy, performance, scalability, etc. As part of our research, we are focusing on a blockchain-based medical application field. The concept is based on the Internet of Things (IoT) and Blockchain, where we employ wearable devices to read user data like blood pressure, heartbeat, and temperature. However, anyone can wear this wearable device which comes up with the problem that it is optional that the data we are storing comes from a valid user. Secondly, we need fast access to data stored in Blockchain, but as the block creation takes 10-12 seconds, we suffer from some delay in response time. In our work, we proposed solutions to these two problems by using authentication while storing data and reduction in the Block creation time.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126055419","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":"Brain Tumor Detection Using YOLOv5 and Faster R-CNN","authors":"Anuhya Kesana, Jayanthi Nallola, Rudra Teja Bootapally, Sireesha Amaraneni, G. Subba Reddy","doi":"10.1109/ViTECoN58111.2023.10157773","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157773","url":null,"abstract":"Brain tumors are viewed as quite possibly the most hazardous problem in the world. Brain tumors spread quickly, and if they are not treated promptly, the patient's chances of survival are slim. Cancer cells can be benign or malignant, which is further subdivided into distinct classes such as meningioma, pituitary, and glioma. Machine-diagnosis-based methods have emerged recently and are able to identify brain cancers by utilizing magnetic resonance imaging. Two deep learning-based approaches for tumor recognition and categorization are included in our proposal, one with the YOLO (You Only Look Once) algorithm and the other using the faster R-CNN. In this case, we used YOLOv5, the fifth version of YOLO. Both methods for object detection rely on deep learning and are essentially convolutional neural networks. YOLOv5 does, however, necessarily require less computational architecture than other computing models. This paper includes a study based on the Kaggle dataset in which both models are trained across the entire dataset, and the model with the highest accuracy is used to detect brain tumors. Because YOLOv5 appears to have significantly higher precision, the dataset is trained and tested, and tumors are detected using a bounding box as well as malignancy classification using pre-trained classes. After careful calculation of the metric values, the final outcomes are shown graphically.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127301721","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}
Gutti Naga Swetha, K. Bharath, B. Ganesh, P. Narasimhulu
{"title":"Avoiding Dynamic Time Error by Implementing Prediction Logic","authors":"Gutti Naga Swetha, K. Bharath, B. Ganesh, P. Narasimhulu","doi":"10.1109/ViTECoN58111.2023.10157358","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157358","url":null,"abstract":"In a flip-flop, the amount of time that elapses between the transitions of the data input and the active edge of the clock is referred to as the device's setup time. In the event that the data being submitted undergoes any changes while this time frame is active, the storage will not be accurate. This is referred to be a breach of the setup time. The minimal amount of time following the active edge of the clock during which data must remain steady is referred to as hold time. Hold time violations will result in the storing of inaccurate data. Techniques known as “time borrowing” are often used in the mitigation of timing mistakes in high performance architectures. The process of changing a flip-flop into a transparent latch on the fly so that time may be taken up by the subsequent stage and setup time violations can be avoided. Nonetheless, timing violations on continuous critical path (CCP) and critical feedback path (CFP) architectures might still occur as a result of their use. An example of a unique dynamic timing error avoidance (DTEA) approach is provided by a static timing analysis. This method begins by making an effort to eliminate timing errors by using the time borrowing technique. including characteristics such as dynamic clock stretching to make it possible for the circuit to run at a high-performance level. According to the results of the FPGA synthesis, the digital implementation of the structure has exceptionally outstanding performance.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114599742","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":"Multi-class Traffic Sign Recognition System Using One-Stage Detector YOLOv5s","authors":"Sachin Dhyani, Vijay Kumar","doi":"10.1109/ViTECoN58111.2023.10157616","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157616","url":null,"abstract":"One of the crucial software elements in the upcoming generation of autonomous vehicles is image recognition. Traditional approaches to image recognition using computer vision and machine learning typically have a lengthy response time. Modern artificial neural network-based methods and designs, including the YOLOv5s algorithm, are able to tackle this issue without suffering precision losses. In this study, we demonstrate how to use the most recent YOLOv5s algorithm to identify traffic signs. We showed the reliability of the method by training the network for 4 traffic sign classes (speed limit, traffic light, crosswalks, stop,).","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121249300","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}