2023 International Conference on Computer Communication and Informatics (ICCCI)最新文献_第3页

Survey On Smart Agriculture Using Iot 利用物联网的智慧农业调查

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128531

B. SakthiKumar, M. Niranjana, M. Abinath, I.Guru Prasath, K. Jugasri, S. Kailash

引用次数: 0

Asthma Disease Risk Prediction Using Machine Learning Techniques 使用机器学习技术预测哮喘疾病风险

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128635

Pyingkodi M, T. K., W. R, Selvaraj P A, K.Ajith Kumar, Aadarsh V, Mariya Arockiya Akash A

{"title":"Asthma Disease Risk Prediction Using Machine Learning Techniques","authors":"Pyingkodi M, T. K., W. R, Selvaraj P A, K.Ajith Kumar, Aadarsh V, Mariya Arockiya Akash A","doi":"10.1109/ICCCI56745.2023.10128635","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128635","url":null,"abstract":"The signs of asthma, a long-term inflammatory condition of the airways, include wheezing, throat tightness, coughing, and breathing difficulties. The attack of an asthma, which can be fatal, is the fast worsening of these symptoms. Another severe, irreversible airflow restriction in the lungs is caused by respiratory COPD, which encompasses emphysema and chronic bronchitis. In this project, a machine learning-based algorithm is for predicting asthma risk is presented (ML). PEFR, which are widely used external tools like peak flow meters and recognized asthma risk predictors, are frequently monitored. This study shows a relationship between the ambient particle matter(PM) and the weather outdoors. According to the best peak flow value each person was able to acquire, the results are divided into two groups: Safe and Risk circumstances. The link between indoor PM and weather data is mapped to the found values using a convolutional neural network (CNN) architecture. The suggested method’s root mean square and mean absolute error accuracy metrics are contrasted with those of current deep neural network (DNN)-based methods. Additionally, the accuracy of the classification methods KNN and SVM are carried out. The new data set’s asthma category may be predicted more accurately thanks to the application of SVM, KNN, and CNN classification. Python 3.7 is the coding language employed.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129126900","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 Peculiar Image Encryption Technique For Mobile Application 一种特殊的移动应用图像加密技术

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128518

R. Krithika, J. Ponsam

{"title":"A Peculiar Image Encryption Technique For Mobile Application","authors":"R. Krithika, J. Ponsam","doi":"10.1109/ICCCI56745.2023.10128518","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128518","url":null,"abstract":"The upgradation in the field of mobile applications is predominantly increasing. Nowadays mobile applications are used in various platforms on one-handled devices in addition, attackers can use similar technology to anonymize their malicious behaviors and hide their identification of behaviors. Thus, security is important. In this project, we are focusing on the precautionary encryption and decryption algorithms like PNSR metric and Elliptic curve Digital signature algorithm which help us to provide secured transmission of a personal image between the mobile stations. Based on these algorithms a defense application will be developed. There are 4 different levels of technology that will be applied in this project which help to improve security transmission. The first level is selecting a secret image. The secret image will support file types like jpg,png. In the second level of security, we encode the image that we get from thefirst level using an encryption algorithm. Here the image quality is measured by using PSNR metric, the third level is finding the LSB, along with 3m (Mean,Mean,Mode) of the image to hide the message inside the cover image. Then the obtained stegnographic image is compressed using GZIP is the final security level. An Elliptic curve, a Digital signature algorithm is used to enhancea security process. Therefore, this method is suggested to send a secret message through applications of special importance across the mobile application.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130682194","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

Classical Review On Stock Prognosis Using Long Short Term Memory 基于长短期记忆的股票预测经典综述

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128350

K. Praneetha, Perela Narayana Nithesh, Pinni Venkata Sai Sumanth Kumar, T. Vignesh

{"title":"Classical Review On Stock Prognosis Using Long Short Term Memory","authors":"K. Praneetha, Perela Narayana Nithesh, Pinni Venkata Sai Sumanth Kumar, T. Vignesh","doi":"10.1109/ICCCI56745.2023.10128350","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128350","url":null,"abstract":"The main plot of this project is to compare different methods that primarily finds the stock prediction. There are so many machine learning and neurocomputing fields to predict the stock values. Stock price forecasting uses machine learning effectively. Various learning methods are available, including Moving Average (MA), K-nearest Neighbors (KNN), LSTM (Long Short Term Memory), and ARIMA.. LSTM is a type of ANN and RNN neural networks. Because in deep learning they are capable of storing the data in memory. But out of this Long Short-Term Memory(LSTM) is unique compares with other. Because it is used to create long term memory. LSTM performs better in big datasets. It has more additional space to store longer information and it stores longer period of time. While compare to other techniques they can’t store more data like LSTM does. In LSTM we use visualization method so, it is easy to compare the data and find the accuracy value. we used apple and google company datasets to perform LSTM. And here in the papers which we used as reference they performed on datasets namely- Chinese stock market data, Yahoo finance dataset(900000), BSE stocks Tick data, LM SCG, 4 year data of NASDAQ,100 stock market data of NASDAQ stocks. LSTM method gave us best accurate value so we choose LSTM method from others. The main objective of this paper is to find the accurate value of stock market using machine learning through best method out of all available. so we choose LSTM method.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123918782","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

Distributed Inference Approach on Massive datasets using MapReduce 基于MapReduce的海量数据集分布式推理方法

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128196

M. Priadarsini, M. Dharani

引用次数: 0

Blockchain Based Crowd Funding 基于区块链的众筹

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128334

R. Naveenkumaran, S. Geetha, Kaushik Selvaraju, C. Kishore, A. Nagha Rathish

{"title":"Blockchain Based Crowd Funding","authors":"R. Naveenkumaran, S. Geetha, Kaushik Selvaraju, C. Kishore, A. Nagha Rathish","doi":"10.1109/ICCCI56745.2023.10128334","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128334","url":null,"abstract":"Crowdfunding is a method of online fundraising process that was initially developed for public members to make modest contributions to support the projects of creative individuals. Crowdfunding uses blockchain technology to offer smart contracts for users. This allows us to offer crowdfunding in a secure, transparent, and safe manner. The task of this work is to provide interactive forms for campaign development and financial contributions. Both campaign makers and donors may develop and support the campaigns by viewing or submitting requests for approval and fulfilling requests using this system. In addition, the donor may be able to see the progress of the funds they provide. All transactions will be recorded on the blockchain and stored as blocks. It is alluring to use smart contracts in blockchain. Without the aid of a trustworthy third party, a blockchain-based agreement must be negotiated, carried out, and enforced amongst unreliable participants. It is essential to develop executable code that runs on the blockchain. Blockchain was initially primarily used as the basis for cryptocurrencies, but in recent years, it has expanded to various industries. Blockchain is anticipated to be the most widely used technology as a green way to conduct internet transactions One application area for blockchain technology is crowdfunding websites. The biggest problem with today’s global crowdfunding market is that campaigns are no longer under strict control, and some crowd- investment efforts have proven fake. By utilizing Ethereum smart contracts on the crowdfunding site, this work aims to allay these worries by assuring that the initiatives may be added within the designated time limit, eliminating fraud, and allowing the contracts to be fully mechanically performed.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123468288","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

Facial Emotion Recognition for Students Using Machine Learning 使用机器学习的学生面部情绪识别

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128425

V. Pandimurugan, Angad Singh, Akash Tiwari

引用次数: 1

System for Detecting Intrusions using Raspberry PI 系统检测入侵使用树莓派

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128487

Dennis Mathew, G. Kirubasri, K. Vijay, I. Eugene Berna, K. Sowmia

{"title":"System for Detecting Intrusions using Raspberry PI","authors":"Dennis Mathew, G. Kirubasri, K. Vijay, I. Eugene Berna, K. Sowmia","doi":"10.1109/ICCCI56745.2023.10128487","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128487","url":null,"abstract":"Home invasions and thefts have gotten far too frequent in recent years. However, it is uncommon for people to be familiar with different systems, such as intrusion detectors, surveillance systems, and so on. The average person finds it challenging to maintain his home secure as a result. CCTV cameras are expensive in surveillance since they employ computers. It sets aside an excessive amount of space for ongoing recording and needs personnel to find irregularities. Our goal is to develop a comprehensive home security system that will help homeowners protect their properties from such disasters. The Raspberry Pi4-based Home Security System project aims to let someone secure their home against burglary and theft in one go. However, the Raspberry Pi system is significantly less expensive, has greater resolution, and has capabilities that use less power than the current system. Here, infrared (IR) sensors are used as straightforward yet effective triggers for human presence. For tiny confidential data area surveillance, this solution is appropriate. i.e., a home office, a bank restroom, etc. The image is taken by the camera and momentarily saved in the Raspberry Pi module whenever motion is detected by the PIR sensor within the room. Applications built on the Internet of Things can be used remotely to monitor activities and receive alerts when motion is detected.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114221934","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

IOT Based Detection of Food And Water Contamination 基于物联网的食品和水污染检测

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128393

R. Ram, Prem Savarinathan, Thenmozhi Karuppasamy, Avila Jayapalan

{"title":"IOT Based Detection of Food And Water Contamination","authors":"R. Ram, Prem Savarinathan, Thenmozhi Karuppasamy, Avila Jayapalan","doi":"10.1109/ICCCI56745.2023.10128393","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128393","url":null,"abstract":"Food has a major role in the promotion of health and prevention of many diseases. With an increase in the population, food quality is being decreased day by day. Nowadays, many inorganic components are mixed with food materials, and many chemicals are used to preserve food to meet food demand. These chemicals contaminate food and lead to many health issues. Water is one of the basic sources for all the living organisms on the earth. Water is also getting contaminated in many ways and this contamination results in the birth of new diseases. To overcome these problems, there is a need for a device to detect the contamination of food and water. Internet of Things (IoT) is growing rapidly and becoming a vast source of information. IoT has a great feature in detecting food and water quality. By connecting the Arduino and sensors the quality of food and water can be detected and by utilizing Wi-Fi module the information can be transmitted. Water samples are collected from various sources like tap, borewell and wells in the local environment. Various Junk food items, fruits and milk quality is tested under food category with the aid of sensors. If contamination has been detected then the information is passed on to the officials in the Department of Food Safety and Drug administration for further action. In this way, effectively checking food and water quality avoids food and water-borne illness and paves a way to lead a healthy life.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114347492","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

An Intelligent System to Assess the Exterior Vehicular Damage based on DCNN 基于DCNN的车辆外部损伤智能评估系统

2023 International Conference on Computer Communication and Informatics (ICCCI) Pub Date : 2023-01-23 DOI: 10.1109/ICCCI56745.2023.10128579

K. Meenakshi, S. Sivasubramanian

{"title":"An Intelligent System to Assess the Exterior Vehicular Damage based on DCNN","authors":"K. Meenakshi, S. Sivasubramanian","doi":"10.1109/ICCCI56745.2023.10128579","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128579","url":null,"abstract":"In today’s world, with all the technological advancements that we have made, the process of car damage detection is a very lengthy process involving a lot manual work. It requires human verification approach which is very slow and leads to an extremely arduous and tardy process, which leads to human error creeping into the results, thereby increasing the hardships of the common man. Proliferation of Indian automobile industry is directly proportional to the car incidents which is also directly proportional to more insurance claims. Insurance companies need to cover many simultaneous claims and solve the issue related to claims leakage. We explore different DNN based techniques for the purpose of the vehicle damage detection which will completely eliminate the large amount of paper work and man power for physical damage estimation and shift this entire process to an efficient AI based solution which can provide a rapid claim process in a shorter time span. The proposed model provides high accuracy confidence scores for the detected damages which are classified on the basis of the 21 vehicle damage classes that we have defined so that there can be an extensive segregation of damages incurred by the vehicle.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116202666","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