Authors : Srushti Bihade; Lakshmi Shainu; Parth Kumthekar; Vedant Paradkar

Volume/Issue : Volume 11 - 2026, Issue 7 - July

Google Scholar : https://tinyurl.com/pc48yhpj

Scribd : https://tinyurl.com/mwj9zymn

DOI : https://doi.org/10.38124/ijisrt/26jul581

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Abstract : Agriculture in drought-prone regions is increasingly challenged by water scarcity, irregular rainfall patterns, and inefficient irrigation practices. Conventional methods such as manual watering, flooding, and timer-based systems often fail to account for crop-specific growth stages and real-time soil moisture conditions. This paper presents Crop AI, a low-cost Internet of Things (IoT)-enabled smart greenhouse irrigation system that integrates soil moisture sensing, water-level monitoring, an ESP8266 microcontroller, and a crop growth-stage database. The system retrieves the required moisture threshold based on the selected crop and its growth stage, compares it with real-time sensor data, and activates irrigation only when necessary. The proposed architecture is designed specifically for small-scale greenhouse farmers operating in drought-prone and resource-constrained environments. This study outlines the system architecture, database design, control workflow, component-level cost, indicative performance comparison, as well as its advantages, limitations, and future scope. The findings indicate that crop-stage-aware irrigation has the potential to reduce unnecessary water consumption and promote sustainable precision agriculture, particularly when further validated through extended field trials.

Keywords : IoT, Smart Irrigation, Precision Agriculture, ESP8266, Soil Moisture Sensor, Crop Database, Greenhouse Automation, Water-Use Efficiency.

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