Recent Trends in Intensive Computing最新文献_第3页

IoT Based Smart Cradle Using PI 基于物联网的智能摇篮使用PI

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210268

Kannan P, A. Devaraj, B.Pradheep T Rajan, Swathira P K, Subhikshaa Jayaranim, Shebna V

{"title":"IoT Based Smart Cradle Using PI","authors":"Kannan P, A. Devaraj, B.Pradheep T Rajan, Swathira P K, Subhikshaa Jayaranim, Shebna V","doi":"10.3233/apc210268","DOIUrl":"https://doi.org/10.3233/apc210268","url":null,"abstract":"In this modern era, parents are busy building their lifestyle, carrier etc. As we know it has now become hard because parents have to take care of their children simultaneously, which paves a lot of work pressure and family pressure especially for women. Health of the child is affected and better care has also reduced. So, in order to handle such situation, we use temperature, Humidity, ultra-sonic Sensor. The conditions of the external atmosphere help to detect increased body temperature, babies voice while crying and their movements while they are continuously moving and also indicates the time for the diaper to be changed. If there are any abnormal activities are observed in baby’s atmosphere. An alert message is sent to the parents. In this system a video camera is attached and operated under the microcontroller’s instruction and it records a video when the motion sensor detects any continuous movements. The recorded video is broadcasted in a display to the parents which helps them to monitor baby in live. And in addition, this system detects and displays the status of the infant and alert the respective guardian by collecting values from sensor like temperature sensor, ultrasonic sensor, and also the location value from raspberry pi.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127632215","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

Content Filtering of Social Media Sites Using Machine Learning Techniques 使用机器学习技术的社交媒体网站内容过滤

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210226

U. Tambe, N.R. Kakad, S. Suryawanshi, S. S. Bhamre

引用次数: 0

Fundus Image Classification Using Convolutional Neural Network 基于卷积神经网络的眼底图像分类

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210277

U. Savitha, Kodali Lahari Chandana, A. Cathrin Sagayam, S. Bhuvaneswari

引用次数: 0

Aero Engine Performance Monitoring Using Least Squares Regression and Spectral Clustering 基于最小二乘回归和谱聚类的航空发动机性能监测

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210217

Kunaal Saxena, M. Nene

引用次数: 0

Blockchain Technology: Rising Trend in Various Applications 区块链技术:各种应用的上升趋势

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210228

Zalte S. S, Patil P. N, Deshmukh S. N, Patil M. G, Dr. Pallavi Katkar

引用次数: 1

A Wi-Fi Based Smart Irrigation Monitoring for an Agricultural Environment 基于Wi-Fi的农业环境智能灌溉监测

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210237

N. Patankar, Manoli Charmal, Nikhil Bhaskar, Swati Janrao, Aniket Kamble

{"title":"A Wi-Fi Based Smart Irrigation Monitoring for an Agricultural Environment","authors":"N. Patankar, Manoli Charmal, Nikhil Bhaskar, Swati Janrao, Aniket Kamble","doi":"10.3233/apc210237","DOIUrl":"https://doi.org/10.3233/apc210237","url":null,"abstract":"A producer who controls irrigation using a smartphone. A firebase that uses weather data to predict when to water crops. Sensors that read how much water is in the soil. From water availability and unpredictable weather patterns to regulations from outside entities, it can be a challenge to irrigate crops. Nowadays IoT has different solutions to overcome with this kind of problem. The particular research targeted successfully by development effected system using NodeMCU, Sensors, firebase, and assertive application. These tools which could conserve a good amount of water, it will become vital to success as the population groves and water availability dries up. The tool works by helping farmers with limited irrigation capacity determine the best time to water their crops. The main ai m of automating the system is to provide a certain amount of water required by crops by monitoring the moisture of soil and surrounding temperature. This obtains with the help of sensors and NodeMCU for interfacing their values. The values are displayed on a mobile application in real-time using Google’s firebase. Irrigation using IoT is a key component of precision agriculture. By changing manual irrigation with automatic valves and systems reduces the human error. Farmer can monitor his crop yield from anywhere at any time.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131916474","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

Highly Secured Dynamic Color QR Pattern Generation for Real Time Application 用于实时应用的高度安全的动态彩色QR模式生成

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210290

R. Sanjjey, S. Abisheak, T. Dineshkumar, M. Kirthan, S. Sivasaravanababu

引用次数: 0

A Systematic Review of Blockchain Technology and Its Applications 区块链技术及其应用系统综述

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210230

Bharati H Naikwadi, K. Kharade, S. Yuvaraj, K. Vengatesan

引用次数: 0

Predicting COD and BOD Parameters of Greywater Using Multivariate Linear Regression 用多元线性回归预测污水COD和BOD参数

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210199

Samir Sadik Shaikh, Rekha Shahapurkar

{"title":"Predicting COD and BOD Parameters of Greywater Using Multivariate Linear Regression","authors":"Samir Sadik Shaikh, Rekha Shahapurkar","doi":"10.3233/apc210199","DOIUrl":"https://doi.org/10.3233/apc210199","url":null,"abstract":"Greywater reuse furthermore, reusing can be an incredible method to get non-consumable water. Since it contains broke down pollutions, greywater can’t be utilized straightforwardly. As an outcome, it is critical to decide the nature of water prior to utilizing it. Body estimations require five days to finish, while COD estimations require only a couple of hours. Not exclusively improve models for evaluating water quality are required; however, a more coordinated methodology is additionally getting more normal. Most of these models require a wide scope of information that isn’t in every case promptly available, making it a costly and tedious activity. Because of different issues in the enlistment with estimation included in water quality boundaries like BOD as well as COD, the principal objective of this investigation is to track down the best multivariate direct relapse models for foreseeing complex water quality outcomes. The code was written in Python for multi-variable information sources, and a Linear Regression Model was created. The projected COD versus estimated COD chart shows that the noticed and expected qualities are practically the same. The R-squared worth was 0.9973. A plot of extended BOD as an element of COD is likewise remembered for the outcome.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120916527","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

Hybrid Parallel Feature Subset Selection for High Dimensional Datasets 高维数据集的混合并行特征子集选择

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210180

Archana Shivdas Sumant, D. Patil

引用次数: 0