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Future Farming

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Artificial Intelligence is vital to the evolution of agriculture into a smart industry. The objective of this book is to inform readers about how artificial intelligence is improving agriculture by exploring its applications. The book addresses several aspects of artificial intelligence applications in smart agriculture including, pest control, disease identification, weed detection, and security. Chapters are contributed by experts in agriculture, computer science and biotechnology. Key Themes: Advanced machine learning techniques for pest control and disease identificationAutomated recognition and classification of plant diseases, focusing on tomatoes and pearl milletIntegration of artificial intelligence for solar-powered robots to identify weeds and damages in vegetablesDevelopment of field prevention systems to deter wild animals in farming areasUtilization of machine learning for weather forecasting to facilitate smart agriculture practicesIntelligent crop planning and precision farming through AI applications>Other features of the book include a list of references and simple summaries in each chapter to distil the information for readers. The book is a primary reference material for courses on automation in agriculture. It can also serve as a handbook for anyone interested in advances in farming.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789815124743
  • Indbinding:
  • Paperback
  • Sideantal:
  • 166
  • Udgivet:
  • 23. oktober 2023
  • Størrelse:
  • 178x11x254 mm.
  • Vægt:
  • 408 g.
Leveringstid: 2-3 uger
Forventet levering: 22. januar 2025
Forlænget returret til d. 31. januar 2025
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Beskrivelse af Future Farming

Artificial Intelligence is vital to the evolution of agriculture into a smart industry. The objective of this book is to inform readers about how artificial intelligence is improving agriculture by exploring its applications. The book addresses several aspects of artificial intelligence applications in smart agriculture including, pest control, disease identification, weed detection, and security. Chapters are contributed by experts in agriculture, computer science and biotechnology. Key Themes: Advanced machine learning techniques for pest control and disease identificationAutomated recognition and classification of plant diseases, focusing on tomatoes and pearl milletIntegration of artificial intelligence for solar-powered robots to identify weeds and damages in vegetablesDevelopment of field prevention systems to deter wild animals in farming areasUtilization of machine learning for weather forecasting to facilitate smart agriculture practicesIntelligent crop planning and precision farming through AI applications>Other features of the book include a list of references and simple summaries in each chapter to distil the information for readers. The book is a primary reference material for courses on automation in agriculture. It can also serve as a handbook for anyone interested in advances in farming.

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