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Research on World Agricultural Economy

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Volume 7 Issue 3 (September 2026)

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Internet of Things-Based Farming's Impact on Sustainable Development, Workforce Skills, and Crop Yield in Tamil Nadu, India

DOI: https://doi.org/10.36956/rwae.v7i3.105330

Received: 14 September 2025 | Revised: 18 October 2025 | Accepted: 26 December 2025 | Published Online: 1 September 2026

Copyright © 2026 Hayder M. Ali, Gayathri Ananthakrishnan, Praveena Nuthakki, Aseel Smerat, Sameh Abdulah, Rajeshkumar G, Samariddin Makhmudov, Sudhakar Sengan. Published by Nan Yang Academy of Sciences Pte. Ltd.

Creative Commons LicenseThis is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.

Abstract

Precision Agriculture Technologies (PAT) have attracted increased attention for the potential to enhance Farm Productivity (FP), Labor Skill (LS), and Environmental Sustainability (ES). The impact of PAT, focusing on farms in Tamil Nadu, India, which have implemented tools such as Global Positioning Systems, Variable Rate Technology, remote sensing, and soil sensors. A comparative analysis of PAT and non-PAT farms highlights significant advances in Crop Yield (CY), Water Use Efficiency (WUE), and cost reduction. The study also conducts a before-and-after analysis of farms that have recently adopted PAT, revealing increases in CY and farmer income (FI), as well as decreases in input costs and labor working hours. An ES impact test determined that nitrogen, phosphorus, and potassium (NPK) is more efficient, the application of pesticides is minimized, and the CO₂ emission levels are reduced. The four most effective PAT factors identified by the probing research are financial, technical, transportation, and profitability. PAT improves ES by boosting CY, minimizing chemical use and water use savings, and reducing costs via decreased energy and resource consumption. Improved FI, reduced expenses for inputs, and higher nutrient levels have been correlated with a 1.2-year boost in income in PAT-using fields. The results of this endeavor will examine how PAT, sensor devices, and machine learning (ML) can be applied to different agricultural contexts to improve ES yields and quality. PAT's increasing profitability and reduced costs balance its initial costs, proving its worth in sustainable farming and India's agricultural development. Return on investment is 1.2 years.

Keywords: Precision Agriculture Technologies, Environmental Sustainability, Sustainable Farming Practices, Crop Yield, Farm Productivity, Machine Learning

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Online ISSN: 2737-4777, Print ISSN: 2737-4785, Published by Nan Yang Academy of Sciences Pte. Ltd.