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{ "item_title" : "Ai-Driven Iot Solutions in Agriculture", "item_author" : [" S. Rakesh Kumar", "N. Gayathri", "Vamsidhar Yendapalli "], "item_description" : "This book introduces a novel approach that combines AI-driven analytics with IoT-enabled systems to provide actionable insights for crop management, resource optimization, and decision-making. Offering fresh perspectives on the integration of artificial intelligence with connected farming technologies, this work highlights practical strategies for boosting efficiency, sustainability, and productivity in modern agriculture. Covering a broad scope from precision farming to predictive maintenance, the book is designed for researchers, practitioners, policymakers, and advanced students. Its applications range from improving yield forecasts to reducing environmental impact, making it a valuable resource for both academic study and real-world agricultural innovation.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/03/205/602/3032056020_b.jpg", "price_data" : { "retail_price" : "199.99", "online_price" : "199.99", "our_price" : "199.99", "club_price" : "199.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Ai-Driven Iot Solutions in Agriculture|S. Rakesh Kumar

Ai-Driven Iot Solutions in Agriculture : New Insights

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Overview

This book introduces a novel approach that combines AI-driven analytics with IoT-enabled systems to provide actionable insights for crop management, resource optimization, and decision-making. Offering fresh perspectives on the integration of artificial intelligence with connected farming technologies, this work highlights practical strategies for boosting efficiency, sustainability, and productivity in modern agriculture. Covering a broad scope from precision farming to predictive maintenance, the book is designed for researchers, practitioners, policymakers, and advanced students. Its applications range from improving yield forecasts to reducing environmental impact, making it a valuable resource for both academic study and real-world agricultural innovation.

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Details

  • ISBN-13: 9783032056023
  • ISBN-10: 3032056020
  • Publisher: Springer
  • Publish Date: November 2025
  • Dimensions: 9.32 x 6.48 x 0.9 inches
  • Shipping Weight: 1.35 pounds
  • Page Count: 303

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