Artificial Intelligence and Smart Agriculture Applications (eBook, ePUB)

Redaktion: Kose, Utku; Bharati, Subrato; Podder, Prajoy; Mondal, M. Rubaiyat Hossain; Prasath, V. B. Surya

• Format: ePub

Produktbeschreibung

An essential resource work for understanding how to design and develop smart applications for present and future problems of the field of agriculture.- Dr. Deepak Gupta, Maharaja Agrasen Institute of Technology, Delhi, India

As a result of the advances in Artificial Intelligence (AI), many aspects of daily life have been transformed by smart digital technology. Advanced intelligent algorithms can provide powerful solutions to real-world problems. Smart applications have become commonplace. All areas of life are being changed by smart tools developed to deal with complex issues challenging both humanity and the earth.

Artificial Intelligence and Smart Agriculture Applications presents the latest smart agriculture applications developed across the globe. It covers a broad array of solutions using data science and AI to attack problems facing agriculture worldwide.

Features:

• Application of drones and sensors in advanced farming
• A cloud-computing model for implementing smart agriculture
• Conversational AI for farmer's advisory communications
• Intelligent fuzzy logic to predict global warming's effect on agriculture
• Machine learning algorithms for mapping soil macronutrient elements variability
• A smart IoT framework for soil fertility enhancement
• AI applications in pest management
• A model using Python for predicting rainfall

The book examines not only present solutions but also potential future outcomes. It looks at the role of AI-based algorithms and the almost infinite combinations of variables for agricultural applications. Researchers, public and private sector representatives, agriculture scientists, and students can use this book to develop sustainable and solutions for smart agriculture. This book's findings are especially important as the planet is facing unprecedented environmental challenges from over-farming and climate change due to global warming.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 355
• Erscheinungstermin: 7. September 2022
• Englisch
• ISBN-13: 9781000644371
• Artikelnr.: 64356957

Autorenporträt

Dr. Utku Kose is Associate Professor in Suleyman Demirel University, Turkey. He has more than 100 publications including articles, authored and edited books, proceedings, and reports. V.B. Surya Prasath is an assistant professor in the Division of Biomedical Informatics at the Cincinnati Children's Hospital Medical Center, and at the Departments of Biomedical Informatics, Electrical Engineering and Computer Science, University of Cincinnati from 2018. M. Rubaiyat Hossain Mondal is a faculty member at the Institute of Information and Communication Technology (IICT) in BUET, Bangladesh. He has published a number of papers in journals of IEEE, IET, Elsevier, Springer, Wiley, De Gruyter, PLOS, and MDPI. Prajoy Podder is currently a researcher at the Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology. He worked as a lecturer in the department of Electrical and Electronic Engineering, Ranada Prasad Shaha University, Narayanganj, Bangladesh. Subrato Bharati is a researcher in the Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh. He is a regular reviewer of a number of international journal including Elsevier, Springer, and Wiley.

Inhaltsangabe

1. Application of Drone and Sensors in Advanced Farming: The Future Smart
Farming Technology. 2. Development and Research of a Greenhouse Monitoring
System. 3. A Cloud-Computing Model for Implementing Smart Agriculture. 4.
Application of Conversational Artificial Intelligence for Farmer's Advisory
and Communication. 5. The Use of an Intelligent Fuzzy Logic Controller to
Predict the Global Warming Effect on Agriculture: The Case of Chickpea (
Cicer arietinum L.) 6. Using Machine Learning Algorithms for Mapping Soil
Macronutrient Elements Variability with Digital Environmental Data in an
Alluvial Plain. 7. A Smart IoT Framework for Soil Fertility Enhancement
Assisted via Deep Neural Networks. 8. Plant Disease Detection with the Help
of Advanced Imaging Sensors. 9. Artificial Intelligence-Aided Phenomics in
High throughput Stress Phenotyping of Plants. 10. Plant Disease Detection
using Hybrid Deep Learning Architecture in Smart Agriculture Application.
11. Classification of Coffee Leaf Diseases through Image Processing
Techniques. 12. The Use of Artificial Intelligence to Model Oil Extraction
Yields from Seeds and Nuts. 13. Applications of Artificial Intelligence in
Pest Management. 14. Applying Clustering Technique for Rainfall Received by
Different District of Maharashtra State. 15. Predicting Rainfall for
Aurangabad Division of Maharashtra by Applying Auto-Regressive Moving
Average Model (ARIMA) Using Python Programming.