ItemArticle

Adaptive Mesh Networking Protocol for Self-Healing Electrochemical Sensor Networks in Environmental Monitoring Applications

Title
Adaptive Mesh Networking Protocol for Self-Healing Electrochemical Sensor Networks in Environmental Monitoring Applications
Creator
Mary, S. A. Sahaaya Arul; Tamilselvi, M.; Londhe, Gaurav Vishnu; Muthevi, Anil Kumar; Rao, K. B. V. Brahma; Muniyandy, Elangovan
Description
Sensor networks for environmental monitoring must be robust, flexible, and long-lasting, and comprehensive reviews and evaluations of adaptive mesh networking protocols for self-healing to enable autonomous operation under challenging environmental conditions are needed. The purpose of this study was to conduct an extensive review and assessment of adaptive mesh networking protocols for the self-healing of electrochemical sensor networks used in environmental monitoring. The Adaptive Mesh Networking Protocols enable the distributed autonomous sensors (distributed over vast areas or through obstructions) to dynamically route their collected data, recover when nodes fail, and extend their life (in real-time). In evaluating adaptive mesh networking protocols, we reviewed several key features, including self-healing mechanisms, adaptive routing algorithms (including their mathematical representations), methods for achieving energy efficiency, and mechanisms for securing data collection from autonomous sensor networks. Our simulation results show that our proposed adaptive mesh networking protocol achieves greater than 98% packet delivery success, even with up to 30% of nodes lost. Furthermore, we have shown that our approach can reduce the energy consumption of autonomous sensors by up to 87.5% compared to existing non-adaptive approaches. Our demonstration of real-time monitoring dashboards and a comprehensive performance analysis of the autonomous sensor networks demonstrates the feasibility of implementing adaptive mesh networking protocols into large-scale environmental monitoring projects. A significant area of focus for future research will be sensor-level self-correction to address bio-fouling remediation. 2026 Taylor & Francis Group, LLC.
Source
Analytical Letters;
Date
01-01-2026
Publisher
Taylor and Francis Ltd.
Subject
Adaptive routing; AODV (Ad-hoc On-demand Distance Vector); electrochemical sensors; energy efficiency; environmental monitoring; LoRaWAN (Long Range Wide Area Network); mesh networking
Coverage
Mary S.A.S.A., Department of AIML & Data Science, School of Engineering and Technology, CHRIST University, Bangalore, India; Tamilselvi M., Department of Computer Science and Engineering, Roever Engineering College, Perambalur, India; Londhe G.V., Symbiosis Institute of Technology, Symbiosis International University, Pune, India; Muthevi A.K., Department of Computer Science and Engineering, Aditya University, Surampalem, India; Rao K.B.V.B., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India; Muniyandy E., Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India, Applied Science Research Center, Applied Science Private University, Amman, Jordan
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 32719; CODEN: ANALB
Format
online
Language
English
Type
Article

Citation

Mary, S. A. Sahaaya Arul; Tamilselvi, M.; Londhe, Gaurav Vishnu; Muthevi, Anil Kumar; Rao, K. B. V. Brahma; Muniyandy, Elangovan, “Adaptive Mesh Networking Protocol for Self-Healing Electrochemical Sensor Networks in Environmental Monitoring Applications,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/22624.

Output Formats