Produktbild: Computational Intelligence in Internet of Agricultural Things
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Computational Intelligence in Internet of Agricultural Things

235,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.08.2025

Abbildungen

VI, 466 p. 151 illus., 134 illus. in color.

Herausgeber

M. G. Sumithra + weitere

Verlag

Springer

Seitenzahl

466

Maße (L/B/H)

23,5/15,5/2,4 cm

Gewicht

795 g

Sprache

Englisch

ISBN

978-3-031-67452-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.08.2025

Abbildungen

VI, 466 p. 151 illus., 134 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

466

Maße (L/B/H)

23,5/15,5/2,4 cm

Gewicht

795 g

Sprache

Englisch

ISBN

978-3-031-67452-5

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Computational Intelligence in Internet of Agricultural Things
  • .- 1: Computational Intelligence and Internet of Things in the Agriculture Sector: An Introduction.

    .- 2: Role of Big Data Analytics in Intelligent Agriculture.

    .- 3: Machine learning-based remote monitoring and predictive analytics system for apple harvest storage: A statistical model based approach.

    .- 4: Revolutionizing Agriculture: Integrating IoT Cloud, And Machine Learning for Smart Farm Monitoring and Precision Agriculture.

    .- 5: Impact of Advanced Sensing Technologies in Agriculture with Soil, Crop, Climate and Farmland-based approaches using Internet of Things.

    .- 6: An analytical approach and concept mapping of agricultural issues using deep learning techniques.

    .- 7: Explainable AI for next generation Agriculture - Current Scenario and Future Prospects.

    .- 8: Barriers to implementing computational intelligence-based agriculture system.

    .- 9: Agri-Chain: A Blockchain-Empowered Smart Solution for Agricultural Industry.

    .- 10: Exploiting Internet of Things and AI-Enabled for Real-Time Decision Support in Precision Farming Practices.

    .- 11: Advancing Plant Disease Detection with Hybrid Models: Vision Transformer and CNN-Based Approaches.

    .- 12: Optimizing Agricultural Risk Management with Hybrid Block-chain and Fog Computing Architectures for Secure and Efficient Data Handling.

    .- 13: Innovating with Quantum Computing Approaches in Block-chain for Enhanced Security and Data Privacy in Agricultural IoT Systems.

    .- 14: Implementing Fog Computing in Precision Agriculture for Real-time Soil Health Monitoring and Data Management.

    .- 15: Empowering Farmers: An AI-Based Solution for Agricultural Challenges.

    .- 16: Artificial Intelligence in Agriculture: Potential Applications and Future Aspects.

    .- 17: Case study on Smart irrigation using Internet of Things and XAI Techniques.