Convergence of cloud computing, AI, and agricultural science /

Bibliographic Details
Corporate Author:	IGI Global Online
Other Authors:	Sharma, Avinash Kumar, 1982- (Editor), Chanderwal, Nitin, 1978- (Editor), Khan, Rijwan, 1981- (Editor)
Format:	eBook
Language:	English
Published:	Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2023]
Series:	Advances in environmental engineering and green technologies (AEEGT) book series.
Subjects:	Agriculture > Data processing. Artificial intelligence > Agricultural applications. Cloud computing. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Preface
Chapter 1. A Systematic Study of Services and Security Model in Cloud Computing: A Brief Overview
Chapter 2. Toxicological Parameters and Risk Assessment of Some Novel Insecticides: An In-Depth Analysis
Chapter 3. Cloud in Digital Government: Problems and Perspectives in the Case of Azerbaijan
Chapter 4. A Comprehensive Study on Smart Farming for Transforming Agriculture Through Cloud and IoT
Chapter 5. Analysing the Applications of Cloud Computing in Smart Agriculture
Chapter 6. Cloud Computing-Based Smart Agriculture
Chapter 7. IoT-Based Smart Agriculture
Chapter 8. Smart Agriculture Resource Allocation and Cost Optimization Using ML in Cloud Computing Environment
Chapter 9. Intelligent Farming Utilizing a Soil Tracking Device
Chapter 10. Artificial Intelligence Applications in Agricultural Sustainability: Enhancing Efficiency and Resilience
Chapter 11. Empowering Agriculture With Conversational AI: An Application for Farmer Advisory and Communication
Chapter 12. Impact of Mandatory Food and Agriculture Laws on the Food Manufacturing Industry: Review of 75 Years of Challenges and Changes
Chapter 13. Mechanized Functioning of Tomato and Lettuce Greenhouses Using IoT and Machine Learning Techniques
Chapter 14. Machine Learning Time Series Models for Tea Pest Looper Infestation in Assam, India
Chapter 15. Crop Disease Prediction Using Deep Learning Algorithms
Chapter 16. Identification of Tomato Plant Disease Using Faster R-CNN and RetinaNet
Compilation of References
About the Contributors
Index.