2022 3rd International Conference on Smart Electronics and Communication (ICOSEC)最新文献_第3页

ICOSEC 2022 Cover Page ICOSEC 2022封面页

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/icosec54921.2022.9952141

引用次数: 0

Genetic Algorithm based Controller Design for Cane Carrier of Sugar Factory 基于遗传算法的糖厂甘蔗运输车控制器设计

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951901

Govind Singh Jethi, S. Sunori, Priyanka Joshi, Amit Mittal, P. Juneja

引用次数: 0

Design and R&D of MIS System and C# Backstage for MIS of Colleges in the Era of Mobile Internet 移动互联网时代高校管理信息系统及c#后台的设计与研发

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951885

Xiubin Chen, Juan Lu, Yuenong Dai

引用次数: 0

Quantitative Model of Online Course Teaching Evaluation Mode based on Multi-view Image Reconstruction Algorithm 基于多视图图像重建算法的在线课程教学评价模式定量模型

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951923

Qian Wu

引用次数: 0

Supervised Learning Algorithm for Water Leakage Detection through the Pipelines 管道漏水检测的监督学习算法

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951871

K. R. Aravind Britto, D. Prasad, S. Ragavendiran, Sarange Shreepad, Nishant Kumar Singh, Avijit Bhowmick, M. Siva Ramkumar

{"title":"Supervised Learning Algorithm for Water Leakage Detection through the Pipelines","authors":"K. R. Aravind Britto, D. Prasad, S. Ragavendiran, Sarange Shreepad, Nishant Kumar Singh, Avijit Bhowmick, M. Siva Ramkumar","doi":"10.1109/ICOSEC54921.2022.9951871","DOIUrl":"https://doi.org/10.1109/ICOSEC54921.2022.9951871","url":null,"abstract":"The water distribution system is an efficient, quick, cost-effective, and ecologically friendly method of providing water.Groundwater pipeline networks frequently lack planning as the population expands.Freshwater is often provided to end customers through a water supply network, which consists of subterranean and above-ground pipelines. The water distribution sector is increasingly concerned about leakage in water pipeline networks. This necessitates substantial development in leakage sensing technologies to both avoid and mitigate the potential of leakage. As a solution to this, in this study,a supervised learning algorithm-based water leakage detection through the pipeline idea is proposed. The dataset required for this study is collected in real-time using a hardware set. The hardware setup consists of a water storage tank that is connected with pipelines thatare directed toward the consumers. The pipeline is fitted with microphones that measure the sound of the water flow through the pipeline and the values are stored in a Data Acquisition (DAQ) module. The values in DAQ are further analyzed by the computer system that is integrated with the DAQ. The dataset is further pre-processed and dimensionally reduced to make them compatible with Machine Learning (ML) models. The ML models used in this study further evaluate and classify the data values and helps in detecting the water leakage in pipelines. The ML model Naïve Bayes used in this study shows an accuracy of 97.5% and has the highest accuracy among the three ML models used in this study and is concluded as the most efficient model among the other ML models.","PeriodicalId":221953,"journal":{"name":"2022 3rd International Conference on Smart Electronics and Communication (ICOSEC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129980591","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

Effectual Gesture Controlled Smart Wheelchair for the Incapacitated 为残疾人设计的有效手势控制智能轮椅

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9952008

R. Niranjana, M. Ibrahim, R. Ajay, V. B. Arunnachalam, R. Krishnan, K. Narayanan

引用次数: 6

Fraud Detection and Management for Telecommunication Systems using Artificial Intelligence (AI) 基于人工智能(AI)的电信系统欺诈检测与管理

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951889

Ritika H J, Mohana

引用次数: 1

Platform Stability Test for Efficient Processing of Land Resource Services based on Amazon AWS Architecture and ISAR Images 基于Amazon AWS架构和ISAR图像的土地资源服务高效处理平台稳定性测试

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951865

Guihua Wang

引用次数: 0

Classification of Rice Leaf using RCNN with Transfer Learning 基于迁移学习的RCNN水稻叶片分类

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951951

K. Iyswaryalakshmi, M. Ramkumar, S. Priyanka, D. Jayakumar

{"title":"Classification of Rice Leaf using RCNN with Transfer Learning","authors":"K. Iyswaryalakshmi, M. Ramkumar, S. Priyanka, D. Jayakumar","doi":"10.1109/ICOSEC54921.2022.9951951","DOIUrl":"https://doi.org/10.1109/ICOSEC54921.2022.9951951","url":null,"abstract":"Bangladesh, as one of the 10 leading rice suppliers and users in the globe, heavily relies on grain to power its economic system and meet its food demand. Rice is one of the world’s most common foods. However, rice production is impeded by a variety of crop illnesses. One of most prevalent paddy diseases is leaf disease. Recognizing leaf illnesses is time-consuming as well as difficult for farmers in remote areas due to the lack of expertise. Despite the presence of experts in some areas, illness detection is achieved by the recognition through human eye, which may result in incorrect diagnosis and requires a lot of effort. The use of an automated process can help to solve these problems and hence having an Artificial Intelligence (AI) system is mandatory. In this study, an AI approach to detect four prevalent rice leaf diseases such as, Blast, Sheath Blight, Tungro, and Brownspot is provided. The input was clear photos of affected rice leaves on a white backdrop. The datasets were getting trained on using a variety of Machine Learning methods after appropriate preprocessing. When applied to the test datasets, the proposed approach attained an accuracy of over 97% after 10-fold cross validation. Moreover, to preserve the rice plants’ healthy and suitable growth, it is vital to detect sickness and administer the needed therapy to the injured plants. Therefore, pesticides and/or fertilizers have been recommended based on the severity of the illness detected.","PeriodicalId":221953,"journal":{"name":"2022 3rd International Conference on Smart Electronics and Communication (ICOSEC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133935114","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 Improved Integrated Solution for Novel Home Security System with various Force Points using BYOD 一个改进的集成解决方案，新型家庭安全系统的各种力点使用BYOD

2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) Pub Date : 2022-10-20 DOI: 10.1109/ICOSEC54921.2022.9951959

A. Aslesha, A. Sivanesh Kumar

引用次数: 0