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صفحه اصلی
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International Conference on Artificial Intelligence; City, Industry and Health
Precision Agriculture with AI-IoT: Optimizing PGPB Biofertilizers for Yield and Sustainability
نویسندگان :
Zarrindokht Emami-Karvani
1
1- Department of Microbiology, Fal.C., Islamic Azad University, Isfahan, Iran
کلمات کلیدی :
AI-IoT integration،biofertilizers،climate resilience،precision farming،sustainable agriculture
چکیده :
Global agriculture is not able to provide food security to 9.8 billion people by 2050 in the face of soil degradation, climate change, and unsustainable agriculture. Traditional plant growth-promoting bacteria (PGPB) biofertilizers have inconsistent field performance, requiring innovation. Objective: This review is on AI and IoT integration with PGPB systems to achieve maximum yield prediction, real-time adaptation, and scalability in sustainable agriculture. Methods: Systematic review of 30+ studies (2016–2025) assessed AI algorithms, IoT architectures, and field trials across agroecosystems, with a focus on hybrid models, sensor networks, and policy frameworks. Key Findings: AI-IoT-PGPB systems boosted yields by 15–30% and cut synthetic fertilizer usage by 20–40%. Real-time microbial monitoring improved prediction accuracy by 12–27%, while blockchain enhanced supply chain transparency. Challenges encountered were sensor lifespan, gaps in data among smallholders, and threats of labor displacement. Implications: Integration increases resilience to climate change, promotes UN Sustainable Development Goals, and reduces agriculture's carbon footprint. Infrastructure, farmer capacity building, and equitable data stewardship should take precedence from policymakers to bridge the adoption gap.
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احسان آقاباباگلی
تعیین خط افزونه با رویکرد بهبود تاب آوری ، توسعه و تقویت ظرفیت خط و باس شبکه انتقال
احمد که کشان - میثم علیمردانی فر - زهرا قوی دست - فرید کعبی
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