Work

An IoT-Based Smart Agriculture System for Real-Time Field Monitoring and Crop Prediction

Year: 2025

Type: article

Abstract: This work presents a smart agriculture system integrating multi-sensor data acquisition (soil moisture, temperature, humidity, and light) with Arduino Mega 2560 and ESP8266 for real-time monitoring and irrigation control. Machine learning (Random Forest Classifier) achieved 87.5% accuracy in crop prediction, improving water efficiency and supporting sustainable farming practices.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.16883333

Authors: Shahad K, Ragipindi Jasritha, Gowreesh, J. K., Rajaputra Bhoomika, Rao, Dr. Panduranga

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W6912375241

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