Conference TEHI, November 07-08-Samarkhand, Uzbekistan
Agriculture & Environment
Project Title:
AI for Sustainable Agriculture, Climate Intelligence, and Environmental Monitoring
Overview:
This project develops AI-driven solutions for sustainable farming, food security, climate resilience, and environmental protection.
Key Research Focus Areas:
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Crop disease and weed detection using deep learning
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IoT-enabled smart farming and crop suitability analysis
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Climate modeling and rainfall prediction
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Emission forecasting and environmental analytics
Current Outcomes:
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Multi-crop disease detection systems
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Adaptive weed classification models
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High-accuracy rainfall and emission prediction tools
Funding & Collaboration Relevance:
Strong alignment with USDA, EPA, NOAA, DOE, and sustainability-focused funding programs.
Published papers:
|
Paper Name |
Keywords |
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wheat disease, deep learning, multi-scale feature extraction, CNN, plant pathology, image classification |
|
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ADeepWeeD: An Adaptive Deep Learning Framework for Weed Species Classification |
weed classification, deep learning, adaptive framework, CNN, precision agriculture, plant identification |
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Internet of Things and AI Powered Crop Suitability Detection System for Sustainable Farming |
IoT, crop suitability, AI, sustainable farming, precision agriculture, sensors, smart farming |
|
Crop Recommendation: A Technology-Driven Approach to Enhancing Agricultural Productivity |
crop recommendation, machine learning, agricultural productivity, smart farming, soil analysis, AI |