2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)最新文献_第9页

Estimating the Chances of Getting Heart Disease using Machine Learning Algorithms 用机器学习算法估计患心脏病的几率

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125925

P. Prasad, Vamsi Kongara, Pavan Kumar Ankireddy, Santosh Jagga, Srinivaas Guduru, Shashank K

{"title":"Estimating the Chances of Getting Heart Disease using Machine Learning Algorithms","authors":"P. Prasad, Vamsi Kongara, Pavan Kumar Ankireddy, Santosh Jagga, Srinivaas Guduru, Shashank K","doi":"10.1109/ICOEI56765.2023.10125925","DOIUrl":"https://doi.org/10.1109/ICOEI56765.2023.10125925","url":null,"abstract":"One of the deadliest illnesses that cause death is heart disease. Worldwide, almost 17 million people died each year because of various heart diseases. To aid in the early diagnosis of heart illness, improved diagnosis, high-risk individuals, and enhanced decision-making for extra treatment and prevention, a prediction model can be proposed. Many academics have looked at the heart disease risk variables and suggested certain machine learning algorithms. However, these models need to be enhanced in order to produce findings that are extremely precise due to the large dimensionality of the data. This study intends to develop a novel framework for accurate heart disease diagnosis. The proposed model can generate precise data for the training model by applying effective approaches for data collection, pre-processing, and transformation. The proposed model employs a combined dataset from the universities of Switzerland, Hungarian, Cleveland, Long Beach VA. This model employs Relief methods for feature selection. Ensemble learning is used to generate novel hybrid classifiers. The outcomes demonstrated that hybrid classifiers performed better than current models that displayed an accuracy of above 95%. These results suggests that the model with relief feature selection and hybrid classifiers may be a more effective approach for predicting heart diseases.","PeriodicalId":168942,"journal":{"name":"2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134437880","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

Wireless Flow and Level Monitoring for Water Treatment Plants in Paper and Pulp Industry 造纸和纸浆工业水处理厂的无线流量和液位监测

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125785

M. N, E. S, H. S, Megha A

引用次数: 0

Design and Implementation of IoT Based Accident Detection and Prevention System 基于物联网的事故检测与预防系统的设计与实现

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125826

S. Karthikeyan, J. Kiruthik, S. Madumitha, R. Manikandan, V. Prakash Raj

{"title":"Design and Implementation of IoT Based Accident Detection and Prevention System","authors":"S. Karthikeyan, J. Kiruthik, S. Madumitha, R. Manikandan, V. Prakash Raj","doi":"10.1109/ICOEI56765.2023.10125826","DOIUrl":"https://doi.org/10.1109/ICOEI56765.2023.10125826","url":null,"abstract":"In the modern world, an increase in the usage of automobiles for commercial purposes has also increased the number of accidents occurring in commercial vehicles, which leads to the loss of life of the people involved in the accident. To minimize the death rates involved in an accident, the people who are met with the accident must claim medical assistance at the correct time. This study is concerned with two set-ups. One set-up is associated with the vehicle, where the use of a MEMS or gyroscopic sensor, a vibration sensor, and a gas sensor integrated with Arduino helps to detect the accident. Here, the location is detected by the GPS module and updated in the cloud by using the ESP8266 Wi-Fi module. If any accident is detected, the RF transmitter circuit sends the signal to the RF receiver. The other configuration is related to the Ambulance which consists of an RF receiver circuit integrated with the NodeMCU microcontroller. When the signal reaches the receiver, NodeMCU retrieves the information from the cloud and displays it on the LCD. Integration of a tracking system with a Radio frequency transmitter and receiver helps build IoT services using embedded systems. The system of providing medical assistance to the people involved in the accident would help us reduce the death rates.","PeriodicalId":168942,"journal":{"name":"2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133919891","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

Design of Crop Recommender System using Machine Learning and IoT 基于机器学习和物联网的作物推荐系统设计

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125963

Josephine Selle Jeyanathan, B. Veerasamy, B. Medha, G. V. Sai, R.Bharath Kumar, Varsha Sahu

{"title":"Design of Crop Recommender System using Machine Learning and IoT","authors":"Josephine Selle Jeyanathan, B. Veerasamy, B. Medha, G. V. Sai, R.Bharath Kumar, Varsha Sahu","doi":"10.1109/ICOEI56765.2023.10125963","DOIUrl":"https://doi.org/10.1109/ICOEI56765.2023.10125963","url":null,"abstract":"Agriculture is one of the key drivers of Indian economy. The primary problem now confronting Indian farmers is that farmers don't choose the right crop based on their land requirements. A significant decline in production is seen as a result. Precision agriculture will provide the farmers with a solution to this problem. To suggest the optimal crop to farmers based on site-specific criteria, precision agriculture uses research data on soil types, features, and crop yields. With the help of an intelligent system, this study aims to help Indian farmers increase crop productivity by selecting the right type of soil. The proposed prototype considers soil characteristics, such as pH value, soil temperature, and soil moisture, as well as environmental factors, such as humidity, as inputs to the machine learning algorithm for decision-making. The output is integrated with the web program known as proteus. The entire prototype is designed using STM32 ARM Processor and simulated using proteus, and the same is implemented using the Nucleo board by integrating the humidity, pH, and temperature sensors for collecting the input data. The result of the prototype is also displayed in the Blynk app as well as the LCD display, where the system recommends the appropriate crop.","PeriodicalId":168942,"journal":{"name":"2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":" 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113950616","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

Minimization of Losses in 119 Bus Radial Distribution Network using PSO Algorithm 基于粒子群算法的119总线径向配电网损耗最小化

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125873

V. Rafi, Sharief Nadendla, V. Nayak, K.Venkata Naga Sai Reddy, G.UmeshSai Kumar, A. Maniteja

引用次数: 0

Face Detection based Secured ATM System with Two Step Verification using Fisher Face Method 基于人脸检测的两步验证安全ATM系统

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125744

V. Praveena, A. S., Anu Sankari S, Girija K, Kirthivarsini M

引用次数: 1

Railway Signalling System using Encoder and Decoder 铁路信号系统的编码器和解码器

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125937

M. Ghute, Ajinkya Barhate, Swejal Dhengle, Yachana Bakal, Sharwari Kawale, Devichand Rathod

引用次数: 1

Real Time Building Crack Visual Measurement System using Metaheuristics with Deep Learning Model 基于深度学习模型的元启发式实时建筑裂缝视觉测量系统

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125931

U. R. Babu, Tarun Gehlot, S. Thenmozhi, S. Chandre, A. Ravitheja, A. Gopi

{"title":"Real Time Building Crack Visual Measurement System using Metaheuristics with Deep Learning Model","authors":"U. R. Babu, Tarun Gehlot, S. Thenmozhi, S. Chandre, A. Ravitheja, A. Gopi","doi":"10.1109/ICOEI56765.2023.10125931","DOIUrl":"https://doi.org/10.1109/ICOEI56765.2023.10125931","url":null,"abstract":"Cracks in concrete allow aggressive chemicals to enter the reinforcement and cause corrosion, affecting reinforced concrete longevity. Crack identification is crucial to damage assessment. Visual examination is the most common concrete infrastructure monitoring method. Inspectors visually estimate flaws using skill, engineering judgment, and experience. However, this process is subjective, time-consuming, and requires access to numerous challenging structures. One progress hinges on improving or combining conventional digital image processing methods. Deep learning (DL) methods like CNN can now overcome image processing's crack detection limitations. This study introduces the Real-Time Building Crack Visual Measurement System utilizing Metaheuristics with Deep Learning (RBCVMS-MDL) model. RBCVMS-MDL detects construction cracks using DL principles. Three main steps are involved in RBCVMS-MDL. First, ResNet is used to build feature vectors. Salp Swarm Algorithm (SSA) also tunes ResNet method hyperparameters Finally, Radial Basis Function (RBF) can detect and classify cracks. RBCVMS-MDL outperforms other methods in crack image dataset performance validation.","PeriodicalId":168942,"journal":{"name":"2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116903594","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

Comparing the Effectiveness of Data Visualization Techniques for Discovering Disease Relationships in a Complex Network Dataset 比较数据可视化技术在复杂网络数据集中发现疾病关系的有效性

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125700

S. S, Sarang Dileep, Rahan Manoj, Adarsh M, Sandhya Harikumar

{"title":"Comparing the Effectiveness of Data Visualization Techniques for Discovering Disease Relationships in a Complex Network Dataset","authors":"S. S, Sarang Dileep, Rahan Manoj, Adarsh M, Sandhya Harikumar","doi":"10.1109/ICOEI56765.2023.10125700","DOIUrl":"https://doi.org/10.1109/ICOEI56765.2023.10125700","url":null,"abstract":"In this study, we compare various data visualization methods for exploring a complicated network dataset containing details on illnesses, symptoms, and safety measures. The dataset was obtained from Kaggle and split into train and test subsets at a 4:1 ratio. It has 269 nodes and 483 edges. To evaluate the network data, we used Neo4j and Gephi, two data visualization tools. The dataset was queried and visually analyzed using Neo4j, and graphical representations of the network were produced using Gephi. We tested the potency of different visualization methods for finding patterns and correlations in the data, including force-directed layouts, node-link diagrams, and matrix views. Moreover, Neo4j's querying capabilities allowed us to analyze sub-networks and their connections in greater detail. Overall, our study shows the value of using a variety of visualization methods to have a deeper understanding of complicated network data. Researchers, medical experts, and public health officials attempting to comprehend and manage illness linkages will find the findings of this study to be quite insightful.","PeriodicalId":168942,"journal":{"name":"2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114658125","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

A Detailed Review on Object Detection Algorithms 目标检测算法的详细综述

2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2023-04-11 DOI: 10.1109/ICOEI56765.2023.10125764

Sonia Setia, A. Shukla, Amartya Raj, Abhimanyu Rathore

引用次数: 0