AGRIASSIST: AI- ENHANCED CROP, FERTILIZER, AND PEST MANAGEMENT SOLUTION
Alt Text: AgriAssist: AI-Enhanced Crop, Fertilizer, and Pest Management Solution
Title: AgriAssist: Revolutionizing Crop and Pest Management with AI
Caption: AI-Powered Farming Tools for Precision Agriculture
Description: Learn how AgriAssist uses Machine Learning and Deep Learning to optimize crop production, manage fertilizers, and detect pests, transforming farming with actionable insights.
Keywords: AgriAssist, crop optimization, pest management, precision agriculture, AI farming solutions
International Journal of Engineering and Techniques – Volume 11 Issue 1, January-February 2025
M. Uday Kiran1, K. Vijay2, B. Sandeep3, B. Navaneetha4, L.V.S.R. Raj Kumer5
1,2,3,4,5Dept. of Computer Science Engineering, Siddartha Institute of Technology and Sciences
Email: 21tq1a6703@siddartha.co.in, vijakoraveni.cse@siddartha.co.in, 21tq1a6704@siddartha.co.in, 21tq1a6706@siddartha.co.in, 21tq1a6733@siddartha.co.in
Abstract
AgriAssist is a web-based platform that leverages Machine Learning (ML) and Deep Learning (DL) to optimize crop production and protect crops through data-driven recommendations. It provides real-time crop selection guidance based on soil and environmental parameters such as nitrogen, phosphorus, potassium, temperature, rainfall, humidity, and pH, ensuring sustainable yield improvement. The platform offers tailored fertilizer recommendations for soil fertility and a pest management system powered by Convolutional Neural Networks (CNN), identifying pests and suggesting effective pesticides with dosage guidelines. AgriAssist bridges the gap between soil analysis and actionable insights, empowering farmers with productivity and sustainability tools…
Keywords
AgriAssist, crop optimization, pest management, precision agriculture, AI farming solutions
How to Cite
M. Uday Kiran, K. Vijay, B. Sandeep, B. Navaneetha, L.V.S.R. Raj Kumer, “AgriAssist: AI-Enhanced Crop, Fertilizer, and Pest Management Solution,” International Journal of Engineering and Techniques, Volume 11, Issue 1, January-February 2025. ISSN 2395-1303
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