Authors :
Dr. K. Kavitha
Volume/Issue :
Volume 10 - 2025, Issue 7 - July
Google Scholar :
https://tinyurl.com/y8esvhj7
DOI :
https://doi.org/10.38124/ijisrt/25jul510
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
Due to the change in land-use practices, deforestation, and climate unexpectedness, soil erosion is becoming more
threatened to the tribal mountainous areas of Kodaikanal. Although indigenous groups have long used traditional soil
conservation techniques, these approaches have not officially recognized and are not very effective in front of contemporary
environmental stresses. Recent years have seen the ability of technical successes to change the ability to completely replace
durable agriculture and soil management techniques, especially in the Internet of Things (IOT), Artificial Intelligence (AI), and
the areas of the Geographical Information System (GIS). However, there is still a lot about how to combine this technique with
traditional knowledge systems for Kodaikanal soil conservation. This review study assesses the suitability of digital technology
for soil conservation in relation to indigenous practices by seriously analyzing national and international literature.
The study exposes gaps in previous researches and suggests a hybrid framework that combines data-operated innovations
with traditional ecological knowledge, especially in steep tribal areas such as Kodaikanal where there are no recorded
technology-acquired soil models. Application of generic AI for landscape-based land-use consultant and erosion modeling, the
manufacture of bilingual mobile platforms for farmer outreach, and potential use of real-time IOT sensors enabling soil health
monitoring is examined. By doing this, the report provides a route for the upcoming multidisciplinary initiatives that prefer
stability, inclusion and community participation. In addition to providing scalable insight to other ecological delicate and
culturally rich places, it emphasizes the need to preserve and improve traditional methods through reference-inconceivable
technical support. With the goal of focusing from erosion to ecological flexibility, this work performs the ground task to develop
the first-time implementation strategy in the Kodaikanal region.
Keywords :
Indigenous Knowledge Systems, Soil Conservation, Technological Integration, Kodaikanal Hills, Tribal Farming Practices, Rural Technology Adoption.
References :
- Bagyaraj, M., & Gurugnanam, B. (2011). Morphometric Analysis of the Kodaikanal Watershed, Tamil Nadu using Remote Sensing and GIS Techniques. Research Journal of Environmental and Earth Sciences, 3(3), 219-222.[Publisher: Maxwell Scientific Organization]
- Uma Maheswari, R., Elangovan, K., & Ramesh, N. (2015). Changes Detection in Land Use and Land Cover Pattern Using Remote Sensing and GIS in Kodaikanal Town. Current Research Journal of Social Sciences, 7(4), 73–78.[Publisher: Maxwell Scientific Organization]
- Sivakami, S., & Rajkumar, R. (2020). Landslide Vulnerability Zone by Weights-of-Evidence Model Using Remote Sensing and GIS in Kodaikanal Taluk, Tamil Nadu, India. International Journal of Engineering Research and Technology (IJERT), 9(3), 1–5.[Publisher: ESRSA Publications]
- Berkes, F. (2000). Rediscovery of Traditional Ecological Knowledge as Adaptive Management. Ecological Applications, 10(5), 1251–1262.[Publisher: Ecological Society of America]
- Mazzocchi, F. (2006). Western Science and Traditional Knowledge: Despite Their Variations, Different Forms of Knowledge Can Learn from Each Other. EMBO Reports, 7(5), 463–466. [Publisher: Nature Publishing Group]
- Tamil Nadu Forest Department Reports (2008–2020). Annual Forest Conservation and Shola Restoration Reports. [Publisher: Government of Tamil Nadu].
Due to the change in land-use practices, deforestation, and climate unexpectedness, soil erosion is becoming more
threatened to the tribal mountainous areas of Kodaikanal. Although indigenous groups have long used traditional soil
conservation techniques, these approaches have not officially recognized and are not very effective in front of contemporary
environmental stresses. Recent years have seen the ability of technical successes to change the ability to completely replace
durable agriculture and soil management techniques, especially in the Internet of Things (IOT), Artificial Intelligence (AI), and
the areas of the Geographical Information System (GIS). However, there is still a lot about how to combine this technique with
traditional knowledge systems for Kodaikanal soil conservation. This review study assesses the suitability of digital technology
for soil conservation in relation to indigenous practices by seriously analyzing national and international literature.
The study exposes gaps in previous researches and suggests a hybrid framework that combines data-operated innovations
with traditional ecological knowledge, especially in steep tribal areas such as Kodaikanal where there are no recorded
technology-acquired soil models. Application of generic AI for landscape-based land-use consultant and erosion modeling, the
manufacture of bilingual mobile platforms for farmer outreach, and potential use of real-time IOT sensors enabling soil health
monitoring is examined. By doing this, the report provides a route for the upcoming multidisciplinary initiatives that prefer
stability, inclusion and community participation. In addition to providing scalable insight to other ecological delicate and
culturally rich places, it emphasizes the need to preserve and improve traditional methods through reference-inconceivable
technical support. With the goal of focusing from erosion to ecological flexibility, this work performs the ground task to develop
the first-time implementation strategy in the Kodaikanal region.
Keywords :
Indigenous Knowledge Systems, Soil Conservation, Technological Integration, Kodaikanal Hills, Tribal Farming Practices, Rural Technology Adoption.