Optimizing environmental monitoring in IoT: integrating DBSCAN with genetic algorithms for enhanced clustering

Abstract

In 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 monitoring
• IoT
• clustering
• DBSCAN
• genetic algorithms

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Data availability statement

Data sharing does not apply to this article as no new data has been created or analyzed in this study.

Additional information

Notes on contributors

S. Regilan

Mr. 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: [email protected].

L.K. Hema

Dr. 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.