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BODHIVRUKSHA JOURNAL OF DIVERSE DISCIPLINE

ISSN: 3139-1486 (Online) | ISSN: 3139-9819 (Print) Impact Factor : 6.21 ESTD Year : 2025
Bi-monthly Multilingual Academic Research Multidisciplinary

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AI-Powered Smart Agriculture System

Department of Artificial Intelligence and Data Science, Ajeenkya DY Patil School of Engineering, Pune, India · India

Abstract

This paper presents the design and prototype evidence for an Internet of Things (IoT)-based smart agriculture system described in the project presentation. The proposed system monitors soil moisture, temperature, humidity, water level, rainfall, and light; an ESP32-S3 is listed as the edge controller. The design connects sensor acquisition and local display with Wi-Fi communication, cloud-based monitoring, proposed AI-assisted decision support, and relay-controlled pump operation. The paper follows the project presentation’s system workflow and hardware inventory, explains the intended data path and control functions, and includes the supplied block diagram, circuit drawing, simulation view, and prototype photograph. The listed prototype components have an approximate total cost of INR 2,680. The presentation does not specify a trained model, cloud service, control thresholds, sensor calibration, test protocol, or measured water-use and accuracy results. Therefore, AI, cloud, and irrigation-efficiency functions are treated as design objectives rather than validated performance. The paper makes no quantitative claim of water savings and identifies the implementation details and experiments needed for reproducible evaluation.

Keywords

Internet of Thingssmart agricultureprecision irrigationESP32-S3soil-moisture sensingautomated irrigation.

How to Cite This Article

Triveni Gaikwad, Samruddhi Ingale, Sujal Chavan, Aditya Bhagwat, Dr. Vishal Puranik. (2026). AI-Powered Smart Agriculture System. Special Issue on Emerging Frontiers in Artificial Intelligence and Multidisciplinary Intelligent Systems.

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