Research on World Agricultural Economy

AI and Sustainable Agriculture Through Cost–Benefit Analysis of Smart Irrigation Systems

Jami Venkata Suman

Department of ECE, GMR Institute of Technology, Rajam 532127, India

Kalisetti Purushotham Prasad Prasad

Department of ECE, Narsimha Reddy Engineering College, Secunderabad 500100, India

A. Sampath Dakshina Murthy

Department of ECE, Vignan’s Institute of Information Technology (A), Duvvada 530049, India

R. Gurunadha

Department of ECE, JNTU‑GV CEV, Vizianagaram 535003, India

Mamidipaka Hema

Department of ECE, JNTU‑GV CEV, Vizianagaram 535003, India

Omprakash Gurrapu

Volvo Trucks North America, Greensboro, NC 27409, USA

DOI: https://doi.org/10.36956/rwae.v6i4.2503

Received: 19 July 2025 | Revised: 12 August 2025 | Accepted: 22 August 2025 | Published Online: 16 September 2025

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Abstract

The advancing role of Artificial Intelligence (AI) and its application in agriculture have disrupted traditional agricultural practices, with smart irrigation systems representing one of the leading technologies enabling sustainable agriculture. Smart irrigation systems utilize real–time data, machine learning algorithms, and predictive analytics to better optimize irrigation water use, limit wasted resources, and improve the yields of crop products. The proposed research will assess the economic and environmental impacts of AI smart irrigation systems with a full costs–benefits analysis. The proposed research considers both the capital cost and operating cost of smart irrigation systems and compares these traditional irrigation practices while also examining the long–term benefits of potential water savings from Smart Irrigation Systems, expanded agricultural production, and reduced human labour. This will give context for measuring the impacts of Smart Irrigation Systems on farm businesses, including both opportunities and barriers to adoption. Additionally, using a formal literature review to lock down existing research and surveys of irrigation farmers to collect a field data set will provide the proposed researchers a collective sample to measure the efficacy of AI smart irrigation systems, identify barriers, compare opportunities, and measure performance under differing climate and soil properties. The research will find high and substantial respective levels of benefits from the implementation of AI–based smart systems, particularly in water–stressed systems with positive impacts on farm profitability, private, and environmental conservation. This research is essential for informing stakeholders of actions and the delivery of AI–enabled solutions in support of more sustainable agricultural practices.

Keywords: Smart Irrigation; Artiϐicial Intelligence; Cost–Beneϐit Analysis; Sustainable Agriculture; Water Manage‑ ment

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