SMARD: A Cost Effective Smart Agro Development Technology for Crops Disease Classification
Tanoy Debnath, Shadman Wadith, and Anichur Rahman

TL;DR
SMARD is a cost-effective smart agricultural technology that leverages machine learning for crop disease classification, providing farmers with vital resources, expert support, and economic benefits to enhance productivity and livelihoods.
Contribution
The paper introduces SMARD, a novel system that combines image-based machine learning with farmer support services to improve crop disease detection and agricultural productivity.
Findings
Achieved 97.3% classification accuracy in crop disease detection.
Attained 96% F1-score, outperforming existing web applications.
Enabled rapid disease recognition to assist farmers in timely interventions.
Abstract
Agriculture has a significant role in a country's economy. The "SMARD" project aims to strengthen the country's agricultural sector by giving farmers with the information and tools they need to solve common difficulties and increase productivity. The project provides farmers with information on crop care, seed selection, and disease management best practices, as well as access to tools for recognizing and treating crop diseases. Farmers can also contact the expert panel through text message, voice call, or video call to purchase fertilizer, seeds, and pesticides at low prices, as well as secure bank loans. The project's goal is to empower farmers and rural communities by providing them with the resources they need to increase crop yields. Additionally, the "SMARD" will not only help farmers and rural communities live better lives, but it will also have a good effect on the economy of…
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Taxonomy
TopicsSmart Agriculture and AI
