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  • Predictive Analytics in Smart Agriculture

    Predictive Analytics in Smart Agriculture by Krishnan, Saravanan; Anand, A.Jose; Prasanth, Narayanan;

      • 20% KEDVEZMÉNY?

      • A kedvezmény csak az 'Értesítés a kedvenc témákról' hírlevelünk címzettjeinek rendeléseire érvényes.
      • Kiadói listaár GBP 49.99
      • Az ár azért becsült, mert a rendelés pillanatában nem lehet pontosan tudni, hogy a beérkezéskor milyen lesz a forint árfolyama az adott termék eredeti devizájához képest. Ha a forint romlana, kissé többet, ha javulna, kissé kevesebbet kell majd fizetnie.

        23 882 Ft (22 745 Ft + 5% áfa)
      • Kedvezmény(ek) 20% (cc. 4 776 Ft off)
      • Kedvezményes ár 19 106 Ft (18 196 Ft + 5% áfa)

    23 882 Ft

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    Beszerezhetőség

    Még nem jelent meg, de rendelhető. A megjelenéstől számított néhány héten belül megérkezik.

    Why don't you give exact delivery time?

    A beszerzés időigényét az eddigi tapasztalatokra alapozva adjuk meg. Azért becsült, mert a terméket külföldről hozzuk be, így a kiadó kiszolgálásának pillanatnyi gyorsaságától is függ. A megadottnál gyorsabb és lassabb szállítás is elképzelhető, de mindent megteszünk, hogy Ön a lehető leghamarabb jusson hozzá a termékhez.

    A termék adatai:

    • Kiadás sorszáma 1
    • Kiadó CRC Press
    • Megjelenés dátuma 2025. december 26.

    • ISBN 9781032488981
    • Kötéstípus Puhakötés
    • Terjedelem312 oldal
    • Méret 234x156 mm
    • Nyelv angol
    • Illusztrációk 23 Illustrations, black & white; 84 Illustrations, color; 16 Halftones, black & white; 68 Halftones, color; 7 Line drawings, black & white; 16 Line drawings, color; 28 Tables, black & white
    • 700

    Kategóriák

    Rövid leírás:

    This book explores computational engineering techniques and applications in agriculture development. Recent technologies such as cloud computing, IoT, big data, and machine learning are focused on for smart agricultural engineering. This book provides practical and use case oriented approaches for IOT-based agricultural systems.

    Több

    Hosszú leírás:

    Predictive Analysis in Smart Agricultureexplores computational engineering techniques and applications in agriculture development. Recent technologies such as cloud computing, IoT, big data, and machine learning are focused on for smart agricultural engineering. The book also provides a case-oriented approach for IoT-based agricultural systems.


    This book deals with all aspects of smart agriculture with state-of-the-art predictive analysis in the complete 360-degree view spectrum. The book includes the concepts of urban and vertical farming using Agro IoT systems and renewable energy sources for modern agriculture trends. It discusses the real-world challenges, complexities in Agro IoT, and advantages of incorporating smart technology. It also presents the rapid advancement of the technologies in the existing Agri model by applying the various techniques. Novel architectural solutions in smart agricultural engineering are the core aspects of this book. Several predictive analysis tools and smart agriculture are also incorporated.


    This book can be used as a textbook for students in predictive analysis, agriculture engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in cloud computing, IoT, big data, machine learning, and deep learning working on smart agriculture applications.

    Több

    Tartalomjegyzék:

    Chapter 1. Farming Assistance Using Machine Learning and Internet of Things



    Chapter 2. Automated Seasonal Crop Mapping and Acreage Estimation Framework Using Machine Learning Algorithms: A Survey



    Chapter 3. Artificial Intelligence in Precision Agriculture: A Systematic Review on Tools, Techniques and Applications



    Chapter 4. Chatbot for Smart Farming using AI and NLP Techniques



    Chapter 5. Soil Analysis and Nutrient Recommendation System Using IoT and Multilayer Perceptron (MLP) Model



    Chapter 6. IoT Enabled Smart Irrigation with Machine Learning Models for Precision Farming



    Chapter 7. Leaf-CAP: A Capsule Network-based Tea Leaf Disease Recognition and Detection



    Chapter 8. Agri Retail Product Management System



    Chapter 9. Challenges and Prospects of Implementing Information and Communication Technology for Small-Scale Farmers. 



    Chapter 10. Navigating Ethical and Legal Challenges in Smart Agriculture: Insights from Farmers



    Chapter 11. Decision Support System for Smart Agriculture in Predictive Analysis



    Chapter 12. Broad Framework of Digital Twins In Agricultural Domain



    Chapter 13. Predictive Analytics of Climate Change: The Future of Global Warming Lies in Data Analytics



    Chapter 14. Applications of Drones in Predictive Analytics



    Chapter 15. Autonomous Unmanned Ground Vehicles (UGVs) in Smart Agriculture

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