Smart AgriSense: AI-Powered Hybrid System for Crop Health Monitoring

P. Devika, S. Anushobini, V. Harini

2025

Abstract

Precision agriculture is essential for enhancing crop yields and sustainability while reducing resource waste. This study presents Smart AgriSense, a hybrid system powered by AI that merges data from pH and electrical conductivity (EC) sensors with Convolutional Neural Networks (CNNs) for the early detection of crop diseases and improved fertilizer recommendations. Unlike traditional image-based AI models or expensive IoT solutions, this method leverages affordable soil sensors to identify abnormalities before any visible symptoms emerge, facilitating timely intervention. The system analyzes real-time data from sensors and plant images to diagnose diseases and suggest accurate treatments, thereby improving decision-making for farmers. A mobile app with Bluetooth functionality ensures easy access to data, even in rural regions with limited internet access. By incorporating AI-driven insights, the proposed system minimizes pesticide usage, optimizes fertilizer applications, and encourages sustainable farming practices, making cutting-edge agricultural technology more accessible and economical for small-scale farmers.

Paper Citation

in Harvard Style

Devika P., Anushobini S. and Harini V. (2025). Smart AgriSense: AI-Powered Hybrid System for Crop Health Monitoring. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 309-315. DOI: 10.5220/0013882000004919

in Bibtex Style

@conference{icrdicct`2525,
author={P. Devika and S. Anushobini and V. Harini},
title={Smart AgriSense: AI-Powered Hybrid System for Crop Health Monitoring},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={309-315},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013882000004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Smart AgriSense: AI-Powered Hybrid System for Crop Health Monitoring
SN - 978-989-758-777-1
AU - Devika P.
AU - Anushobini S.
AU - Harini V.
PY - 2025
SP - 309
EP - 315
DO - 10.5220/0013882000004919
PB - SciTePress