2023 International Conference on Emerging Smart Computing and Informatics (ESCI)最新文献_第4页

Design and Implementation of Crosstalk Noise Avoidance by using Advanced Test Adapted Shielding for high speed vlsi circuits 高速vlsi电路中基于先进测试适应屏蔽的串扰噪声避免设计与实现

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10100085

B. Obulesu, K. V. Raju, P. S. Sumanth, A. Vamsi, C. Kiran

引用次数: 0

Self- Regulated Robotic Illuminant Using NodeMcu(ESP8266) 采用NodeMcu(ESP8266)的自动调节机器人光源

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099620

Vijay Gaikwad, Manasi Doiphode, Mandar Gatke, Gaurav Moona, Chinmay Gavit, Pranjal Ghuge

引用次数: 0

Cloud based Single Shot Detector Model for Speed Breaker Detection 基于云的高速断路器单次检测模型

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099534

Shital Pawar, Siddharth Nahar, Mohd. Daanish Shaikh, Vishwesh Meher, Sanskruti Narwane

引用次数: 1

Rapid Detection of Pilgrims Whereabouts During Hajj and Umrah by Wireless Communication Framework : An application AI and Deep Learning 基于AI和深度学习的无线通信框架快速检测朝觐和朝圣期间朝觐者行踪

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099969

Mohammed Alhameed, Mohammad Alamgir Hossain

{"title":"Rapid Detection of Pilgrims Whereabouts During Hajj and Umrah by Wireless Communication Framework : An application AI and Deep Learning","authors":"Mohammed Alhameed, Mohammad Alamgir Hossain","doi":"10.1109/ESCI56872.2023.10099969","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099969","url":null,"abstract":"Human injuries and deaths occur often during public events like concerts, religious services, and political rallies because of a lack of proper crowd safety oversight. A small disaster can trigger panic in a huge crowd. Many intelligent video surveillance solutions can identify things, but despite the recent developments in artificial intelligence approaches and deep learning processes, it is very probable to track congested crowds and their mobility to avoid future detection disasters. Searching for points of interest makes use of movement analytics and classification to provide a superior platform for monitoring large crowds. The purpose of point-of-interest explorations is to aid in the management of the safety of moveable crowd events by assisting in the prediction and prevention of future disasters through the classification and analysis of real-time information gathered from crowds. Current surveillance cameras are insufficient for monitoring large crowds in outdoor locations due to their inability to scale. We believe that by using our proposed crowd analysis strategy, we may help enhance the current state of crowd safety management. Among the many aspects of crowd motion, we pay special attention to the difficulties of determining the identity, velocity, and direction of individuals inside the group. We then used these crowd-level semantics to monitor test POI searches in both a controlled lab environment and a real-world crowd. Findings from this study imply that POI searching can be utilized to help prevent harmful circumstances brought on by the movement of large crowds by recognizing the characteristics of mobile crowds in real time.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116473469","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

Learning Aided Intelligent Mechanism for Channel Estimation in 5G Wireless Networks 5G无线网络中信道估计的学习辅助智能机制

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10100184

Sakhshra Monga, A. Taneja, N. Saluja, R. Garg

{"title":"Learning Aided Intelligent Mechanism for Channel Estimation in 5G Wireless Networks","authors":"Sakhshra Monga, A. Taneja, N. Saluja, R. Garg","doi":"10.1109/ESCI56872.2023.10100184","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100184","url":null,"abstract":"The attenuation of signals due to propagation environment is the major challenge of wireless communication which results in frequent call drops, reduced signal strength and low transmission rates. The propagation channel often degrades the signal quality at the receiver due to channel effects including fading, shadowing, path loss and other overhead. The propagation channel and its successful estimation is very important for ensuring communication reliability in next generation wireless systems. This paper presents an intelligent mechanism based on deep learning to estimate the wireless channel such that the system spectral efficiency is enhanced. The impact of signal distortion due to hardware effects is also considered. Further, the proposed scheme is compared with the conventional LMMSE channel estimation scheme. Also, to extract the data using the estimated channel, the performance of proposed scheme is evaluated using three receivers namely, RZF, MMSE and modified MMSE. It is observed that the proposed scheme outperforms the LMMSE scheme in terms of normalised mean square error (NMSE) by 14.43% and by 27.16% in the absence of distortion. In the end, the performance comparison with the system with known perfect channel state information (CSI) is also performed.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126788813","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

Hand Landmark Distance Based Sign Language Recognition using MediaPipe 使用MediaPipe的基于手势标志距离的手语识别

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10100061

P. K, Sandesh B.J

{"title":"Hand Landmark Distance Based Sign Language Recognition using MediaPipe","authors":"P. K, Sandesh B.J","doi":"10.1109/ESCI56872.2023.10100061","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100061","url":null,"abstract":"The deaf and hard-of-hearing community uses sign language for communication and interaction with the external world. Sign language recognition has been an active area of research for many years, and there has been progress in both sensor-based and vision-based methods. Sensor-based methods, such as those that use gloves or other wearable devices, have historically been more accurate, but vision-based methods are becoming more prevalent due to their cost-effectiveness. The study aimed to recognize sign language words using hand pictures captured by a web camera. The mediapipe hands method was used to estimate hand landmarks, and features were generated from the distances between the landmarks. Support Vector Machine (SVM) classifiers were used for character and words classification. The study used its own dataset and it compared different scaling factors, including the distances from positions 0 to 17, 5 to 17, and 0 to 12, to determine which one worked best. The best results were found using the palm size distance (o–9). The proposed approach is economically feasible and computationally simple, requiring no specialized equipment.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116789276","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: 1

Online Transaction Anomaly Detection Model for Credit Card Usage Using Machine Learning Classifiers 基于机器学习分类器的信用卡在线交易异常检测模型

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10100152

B. B. Jayasingh, G. B. Sri

{"title":"Online Transaction Anomaly Detection Model for Credit Card Usage Using Machine Learning Classifiers","authors":"B. B. Jayasingh, G. B. Sri","doi":"10.1109/ESCI56872.2023.10100152","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100152","url":null,"abstract":"The methods for payment of an online transaction are credit or debit card, online bank transfer, e-wallets, mobile payments, etc. The process of electronic fund transfer is secure, and password protected, as claimed by the vendors. The security threats for all payment methods exist with an intention, like credit and debit card frauds. Monitoring fraudulent activities becomes more important as the number of online transactions for credit card usage grows over time. The detection of deviations from the large number of transactions in cases of frauds in credit card is desired using the classifiers of machine learning. We proposed to develop a Transaction Anomaly Detection (TAD) model for online transactions during credit card usage by customers using machine learning. The model is built to exploit and expose fraudulent transactions during online transactions at e-commerce sites. This work considers a data set from kaagle.com that has 28,4807 records of credit card transactions online with a class label. The proposed TAD model applies various machine learning algorithms to calculate the performance metrics and finds an efficient algorithm for detecting online transaction anomalies with good accuracy and recall. We observed that the XGB Classifier classifies the fraudulent transactions with an accuracy of 99.96% and a recall of 83%, which is the best suitable algorithm for this dataset.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132554122","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

Machine Learning Based Problem Solving Approach in Green Computing 绿色计算中基于机器学习的问题解决方法

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099977

S. Bakre, A. Shiralkar, S. Shelar, Suchita Ingle

{"title":"Machine Learning Based Problem Solving Approach in Green Computing","authors":"S. Bakre, A. Shiralkar, S. Shelar, Suchita Ingle","doi":"10.1109/ESCI56872.2023.10099977","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099977","url":null,"abstract":"The issues related to conventional generation of electricity arethe matter of concern for power sector today. These include diminishing stock of coal over a period of time, unavailability of good quality coal, non-sustainable issues, ash handling problems etc. Green energy is the alternative to overcome these problems. The green energy is sustainable, renewable and economical. In India, the existing ratio of conventional to non-conventional generation as on 30th June 2022 is 72:28%. It is required to further improve this ratio to the tune of 60:40%. The performance of the green energy systems can be optimized by AI ML based green computing. Under the umbrella of AI, several technologies have been emerged. These technologies are machine learning, deep learning, data analytics, robotics, neural networks, expert systems, fuzzy logic systems, natural language processing, genetic algorithms etc. The green computing can be made more effective through research as regards how to use these technologies. In this paper, a novice techniques of AI ML based green computing have been proposed. Python programming language is used as a back end programming tool. The proposed methods are simple, cost effective and feasible.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132825793","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

Blockchain Security Implementation using Python with NB-IoT deployment in Food Supply Chain 在食品供应链中使用Python和NB-IoT部署区块链安全实现

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10100139

Chand Pasha Mohammed, Shakti Raj Chopra

{"title":"Blockchain Security Implementation using Python with NB-IoT deployment in Food Supply Chain","authors":"Chand Pasha Mohammed, Shakti Raj Chopra","doi":"10.1109/ESCI56872.2023.10100139","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100139","url":null,"abstract":"Both academia and Industrialists are paying keen attention to the Narrow Band Internet of Things (NB-IoT) developments in the modern era. While the Narrow Band Internet of Things is gradually being adapted for commercial purposes, it continues to raise a slew of security concerns, including those around authentication and privacy. Because blockchain technology incorporates a framework for maintaining confidence, auditing, and openness, it can be a promising tool for ensuring the Network's data exchange is secure. To enhance the level of security afforded narrowband data and to maintain their accuracy and transparency. We leverage the advantages of blockchain technology with Narrow Band Internet of Things (NB-IoT) with Food supply chain management. The system identifies the damaged agricultural product during the transportation between the Manufacturer to the Retailer and executes the python program to find the damaged product during the transportation that is used to authenticate data and generate the blockchain our scheme is deemed to possess attractive confidentiality, authentication, accountability, and quality characteristics, rendering it an ideal method for secure transportation with traceability future added in all-time possible in a decentralized and distributed manner using sha-256 secure algorithm in blockchain technology and narrowband internet of things.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133407745","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: 1

A Novel Approach to Maze Solving Algorithm 一种新的迷宫求解算法

2023 International Conference on Emerging Smart Computing and Informatics (ESCI) Pub Date : 2023-03-01 DOI: 10.1109/ESCI56872.2023.10099728

Yash Gajanan Pame, V. G. Kottawar, Yogeshwari V Mahajan

引用次数: 0