Intelligent Farming Assistant: Precision Agriculture and Disease Diagnosis

Bhavish PK , Savin , Dainik B L , Lavitha Lobo

Intelligent , farming , ai , assistant

Abstract—Agriculture continues to be the primary livelihood for millions in developing nations, yet smallholder and urban farmers face challenges such as low productivity, inefficient resource use, and limited access to modern technologies. This paper introduces an AI-driven Smart Farming Assistant, an integrated and cost-effective platform that combines Internet of Things (IoT) and Artificial Intelligence (AI) to support datadriven decision-making in agriculture. IoT sensors capture realtime environmental data such as soil moisture, temperature, and humidity, while models for machine learning offer tailored crop and fertilizer recommendations. Deep learning-based image analysis enables early plant disease detection. Designed with affordability and accessibility in mind, the system empowers smallholder farmers to increase yield, optimize resources, and adopt sustainable practices. This study details the system’s architecture, implementation, experimental results, and highlights future enhancements to improve scalability and functionality. Index Terms—Smart farming, precision agriculture, IoT, machine learning, soil monitoring, crop recommendation, plant disease detection, sustainability

Published Paper   E-Certificate

"Intelligent Farming Assistant: Precision Agriculture and Disease Diagnosis", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 9, page no.a45-a49, September-2025, Available :https://ijsdr.org/papers/IJSDR2509006.pdf

Volume 10 Issue 9, September-2025

Pages : a45-a49

Paper Reg. ID: IJSDR_304766

Published Paper Id: IJSDR2509006

Downloads: 00099

Research Area: Science and Technology

Country: Mangalore, Dakshina Kannada , Karnataka , India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2509006

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2509006

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition