优化物联网中的环境监测:将DBSCAN与遗传算法集成以增强聚类

S. Regilan, L.K. Hema
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Through a repetitive process involving selection, crossover, and mutation, GA refines parameter settings based on the quality of environmental clustering as assessed by fitness metrics. Our approach is tailored specifically for IoT deployments in environmental monitoring, which involve collecting data from sensor nodes and integrating DBSCAN and GA. We’ve paid special attention to choosing an appropriate distance metric and fine-tuning DBSCAN parameters such as epsilon (ε) and minPts to match the unique needs of environmental monitoring applications. Furthermore, we’ve taken energy efficiency into account by implementing energy-aware node selection and optimizing cluster formation to minimize energy consumption.KEYWORDS: Environmental monitoringIoTclusteringDBSCANgenetic algorithms Disclosure statementNo potential conflict of interest was reported by the author(s).Ethical approvalThis article does not contain any studies with human participants performed by any of the authors.Data availability statementData sharing does not apply to this article as no new data has been created or analyzed in this study.Additional informationNotes on contributorsS. RegilanMr. S. Regilan working as a Research Scholar in the Department of Electronics and Communication Engineering. He has a track record of successful teaching, education reform and has been teaching Students for decades. He Completed his B.E in Electronics and Communication Engineering Department, in Bharath Niketan Engineering College, Anna University on 2011; M.E in Electronics and Communication Engineering Department, in Aarupadai Veedu Institute of Technology, Vinayaka Missions Research Foundation, Chennai on 2015. Pursuing Ph.D in Department of Electronics and Communication Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Missions Research Foundation, Chennai. He worked various recognized Institutions from 2011. He had 10+ years of academic experiences in the field of Electronics and Communication Engineering. He is member in various professional bodies like ISTE, IEEE societies. He participated and Presented many International & National Conferences/Workshop/Seminar/ Webinar in the field of Electronics and Communication Engineering. He published and indexed 5 papers in reputed journals under Scopus with good citations indexed. Mail id: regilan.research@avit.ac.in.L.K. HemaDr. L. K. 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引用次数: 0

摘要

在我们的研究中,我们引入了一种先进的聚类方法,用于基于物联网的环境监测。我们结合了两种强大的技术,基于密度的噪声应用空间聚类(DBSCAN)和遗传算法(GA),创建了一种称为EC-GAD(使用遗传算法和DBSCAN的增强型聚类)的专门方法。该集成系统模型依赖于DBSCAN,这是一种强大的聚类算法,能够处理不规则形状和变化的数据密度,根据传感器节点的物理距离对其进行分组。为了提高聚类性能,我们利用遗传算法来优化DBSCAN的参数。通过包括选择、交叉和突变在内的重复过程,遗传算法根据适应度指标评估的环境聚类质量来优化参数设置。我们的方法是专门为环境监测中的物联网部署量身定制的,其中包括从传感器节点收集数据并集成DBSCAN和GA。我们特别注意选择合适的距离度量和微调DBSCAN参数,如ε (ε)和minPts,以满足环境监测应用的独特需求。此外,我们还考虑了能源效率,通过实现能量感知节点选择和优化集群形成来最小化能源消耗。关键词:环境监测;物联网;聚类;伦理批准:本文不包含任何作者进行的任何人类参与者的研究。数据可用性声明数据共享不适用于本文,因为本研究中没有创建或分析新的数据。附加信息:关于贡献者的说明。RegilanMr。S. Regilan是电子与通信工程系的研究学者。他有成功的教学记录,教育改革,并已教学生几十年。他于2011年在Anna University Bharath Niketan Engineering College获得电子与通信工程系学士学位;2015年毕业于印度金奈,印度理工学院,Vinayaka任务研究基金会,电子与通信工程系。就读于印度金奈印度理工学院电子与通信工程系博士学位,Vinayaka任务研究基金会。自2011年起,他在多个公认的机构工作。他在电子与通信工程领域有10多年的学术经验。他是ISTE, IEEE等多个专业团体的成员。他参加并发表了电子与通信工程领域的许多国际和国内会议/研讨会/研讨会/网络研讨会。他在Scopus的知名期刊上发表并收录了5篇论文,引文索引良好。邮件id: regilan.research@avit.ac.in.L.K。HemaDr。何立凯,电子与通信工程系教授、主任。她有成功的教学记录,教育改革,并已教学生几十年。他在电子与通信工程领域有25年以上的学术经验。她是ISTE, IEEE, IETE等多个专业团体的成员。她参加并发表了许多电子与通信工程领域的国际和国内会议/研讨会/研讨会/网络研讨会。她在Scopus知名期刊上发表并索引了40篇论文,并索引了良好的引文。
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Optimizing environmental monitoring in IoT: integrating DBSCAN with genetic algorithms for enhanced clustering
AbstractIn our study, we introduce an advanced clustering method designed for IoT-based environmental monitoring. We’ve combined two powerful techniques, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithms (GA), to create a specialized approach called EC-GAD (Enhanced-Clustering using Genetic Algorithms and DBSCAN). This integrated system model relies on DBSCAN, a robust clustering algorithm capable of handling irregular shapes and varying data densities, to group sensor nodes based on their physical proximity. To improve clustering performance, we’ve harnessed Genetic Algorithms to optimize the parameters of DBSCAN. Through a repetitive process involving selection, crossover, and mutation, GA refines parameter settings based on the quality of environmental clustering as assessed by fitness metrics. Our approach is tailored specifically for IoT deployments in environmental monitoring, which involve collecting data from sensor nodes and integrating DBSCAN and GA. We’ve paid special attention to choosing an appropriate distance metric and fine-tuning DBSCAN parameters such as epsilon (ε) and minPts to match the unique needs of environmental monitoring applications. Furthermore, we’ve taken energy efficiency into account by implementing energy-aware node selection and optimizing cluster formation to minimize energy consumption.KEYWORDS: Environmental monitoringIoTclusteringDBSCANgenetic algorithms Disclosure statementNo potential conflict of interest was reported by the author(s).Ethical approvalThis article does not contain any studies with human participants performed by any of the authors.Data availability statementData sharing does not apply to this article as no new data has been created or analyzed in this study.Additional informationNotes on contributorsS. RegilanMr. S. Regilan working as a Research Scholar in the Department of Electronics and Communication Engineering. He has a track record of successful teaching, education reform and has been teaching Students for decades. He Completed his B.E in Electronics and Communication Engineering Department, in Bharath Niketan Engineering College, Anna University on 2011; M.E in Electronics and Communication Engineering Department, in Aarupadai Veedu Institute of Technology, Vinayaka Missions Research Foundation, Chennai on 2015. Pursuing Ph.D in Department of Electronics and Communication Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Missions Research Foundation, Chennai. He worked various recognized Institutions from 2011. He had 10+ years of academic experiences in the field of Electronics and Communication Engineering. He is member in various professional bodies like ISTE, IEEE societies. He participated and Presented many International & National Conferences/Workshop/Seminar/ Webinar in the field of Electronics and Communication Engineering. He published and indexed 5 papers in reputed journals under Scopus with good citations indexed. Mail id: regilan.research@avit.ac.in.L.K. HemaDr. L. K. Hema working as a Professor and HOD in the Department of Electronics and Communication Engineering. She has a track record of successful teaching, education reform and has been teaching Students for decades. He had 25+ years of academic experiences in the field of Electronics and Communication Engineering. She is member in various professional bodies like ISTE, IEEE, IETE societies. She participated and Presented many International & National Conferences/Workshop/Seminar/Webinar in the field of Electronics and Communication Engineering. She published and indexed 40 papers in reputed journals under Scopus with good citations indexed.
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来源期刊
International Journal of Computers and Applications
International Journal of Computers and Applications Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
4.70
自引率
0.00%
发文量
20
期刊介绍: The International Journal of Computers and Applications (IJCA) is a unique platform for publishing novel ideas, research outcomes and fundamental advances in all aspects of Computer Science, Computer Engineering, and Computer Applications. This is a peer-reviewed international journal with a vision to provide the academic and industrial community a platform for presenting original research ideas and applications. IJCA welcomes four special types of papers in addition to the regular research papers within its scope: (a) Papers for which all results could be easily reproducible. For such papers, the authors will be asked to upload "instructions for reproduction'''', possibly with the source codes or stable URLs (from where the codes could be downloaded). (b) Papers with negative results. For such papers, the experimental setting and negative results must be presented in detail. Also, why the negative results are important for the research community must be explained clearly. The rationale behind this kind of paper is that this would help researchers choose the correct approaches to solve problems and avoid the (already worked out) failed approaches. (c) Detailed report, case study and literature review articles about innovative software / hardware, new technology, high impact computer applications and future development with sufficient background and subject coverage. (d) Special issue papers focussing on a particular theme with significant importance or papers selected from a relevant conference with sufficient improvement and new material to differentiate from the papers published in a conference proceedings.
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