ItemArticle

ENHANCING FOREST ECOSYSTEM RESILIENCE TO CLIMATE CHANGE WITH VANET AND INTEGRATED NATURAL RESOURCES MODELLING

Title
ENHANCING FOREST ECOSYSTEM RESILIENCE TO CLIMATE CHANGE WITH VANET AND INTEGRATED NATURAL RESOURCES MODELLING
Creator
Satish N.; Premkumar M.; Yuvaraj N.; Anand R.; Suganthi D.; Acharjee P.B.; Rajaram A.
Description
Forest ecosystems are immediately threatened by rising global temperatures and changing climatic patterns. Periodic assessments also contribute to a reduction in the frequency of monitor-ing, which could cause environmental changes to go unnoticed. This work develops a novel real-time monitoring and early warning system to meet this difficulty. By integrating Vehicular Ad Hoc Networks (VANET) with sophisticated natural resources modelling, the proposed method aims to revolutionise the way forest ecosystems are managed. This study strives to design and implement a comprehensive system that harnesses the power of VANET to collect real-time data from sensors deployed on vehicles, and integrates advanced modelling to predict, assess, and mitigate risks to forest ecosystems. The proposed method involves deploying a network of vehicles equipped with environmental sensors within VANET. These sensors continuously collect data on crucial environmental parameters, such as temperature, humidity, air quality, and spatial information. The data are transmitted through a secure VANET communication protocol to a centralised processing unit, where it is integrated with climate models and ecosystem dynamics models. Resilience metrics and thresholds are defined to trigger a tiered early warning system. Preliminary testing of the system demonstrates promising accuracy and responsiveness. The integrated approach allows for dynamic risk assessment, enabling the identification of potential threats such as extreme weather events, invasive species, or disease outbreaks. Early warnings prompt adaptive management strategies, showcasing the systems potential to significantly enhance forest ecosystem resilience. This research presents a pioneering solution to the escalating challenges faced by forest ecosystems in the time of climate change. The real-time monitoring, early warning system, amalgamating VANET and integrated modelling, stand as a robust tool for forest managers, policymakers, and communities to proactively address environmental changes. The findings underscore the systems potential to transform forest management practices, marking a critical step toward sustainable and resilient ecosystems. 2024, Scibulcom Ltd. All rights reserved.
Source
Journal of Environmental Protection and Ecology, Vol-25, No. 1, pp. 247-256.
Date
2024-01-01
Publisher
Scibulcom Ltd.
Subject
adaptive management; climate change; early warning system; environmental sensors; forest ecosystems; integrated modelling; Vehicular Ad Hoc Networks
Coverage
Satish N., Department of Information Technology, Mahendra Institute of Technology, Mallasamudharam, Namakkal, India; Premkumar M., Department of Information Technology, Mahendra Institute of Technology, Mallasamudharam, Namakkal, India; Yuvaraj N., Department of Computer Science and Engineering, KSR College of Engineering, Namakkal, Thiruchengode, India; Anand R., Department of Computer Science and Engineering, Prathyusha Engineering College, Thiruvallur, Tamil Nadu, Aranvoyalkuppam, India; Suganthi D., Department of Computer Science, Saveetha College of Liberal Arts and Sciences, Thandalam, Chennai, India; Acharjee P.B., CHRIST University, Lavasa Campus, Pune, India; Rajaram A., Department of Electronics and Communication Engineering, E.G.S Pillay Engineering College, Tamil Nadu, Nagapattinam, 611 002, India
Rights
Restricted Access
Relation
ISSN: 13115065
Format
Online
Language
English
Type
Article

Collection

Articles

Citation

Satish N.; Premkumar M.; Yuvaraj N.; Anand R.; Suganthi D.; Acharjee P.B.; Rajaram A., “ENHANCING FOREST ECOSYSTEM RESILIENCE TO CLIMATE CHANGE WITH VANET AND INTEGRATED NATURAL RESOURCES MODELLING,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/13747.

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