IoT and AI in Agriculture Self- sufficiency in Food Production to Achieve Society 5.0 and SDG's Globally
tarafından
 
Ahamed, Tofael. editor.

Başlık
IoT and AI in Agriculture Self- sufficiency in Food Production to Achieve Society 5.0 and SDG's Globally

Yazar
Ahamed, Tofael. editor.

ISBN
9789811981135

Basım Bilgisi
1st ed. 2023.

Fiziksel Tanımlama
XVII, 461 p. 1 illus. online resource.

İçerik
Chapter 1. IoT x AI: Introducing Agricultural Innovation for Global Food Production -- Chapter 2. Transforming Controlled Environment Plant Production toward Circular Bioeconomy Systems -- Chapter 3. Artificial Lighting Systems for Plant Growth and Development in Indoor Farming -- Chapter 4. An IoT-based Precision Irrigation System to Optimize Plant Water Requirements for Indoor and Outdoor Farming Systems -- Chapter 5. Artificial Intelligence & Internet of Things: Application in Urban Water Management -- Chapter 6.Purification of Agricultural Polluted Water Using Solar Distillation and Hot Water Producing with Continuous Monitoring Based on IoT -- Chapter 7. Long Range Wide Area Network (LoRaWAN) for Oil Palm Soil Monitoring -- Chapter 8. Application of Smart Machine Vision in Agriculture, Forestry, Fishery, and Animal Husbandry -- Chapter 9. Artificial Intelligence in Agriculture: Commitment to Establish Society 5.0 -- Chapter 10. Potentials of Deep Learning Frameworks for Tree Trunk Detection in Orchard to Enable Autonomous Navigation System -- Chapter 11. Real Time Pear Fruit Detection and Counting Using YOLOv4 Models and Deep SORT -- Chapter 12. Pear Recognition in an Orchard from 3D Stereo Camera Datasets to Develop an Autonomous Mechanism Compared with Deep Learning Algorithms -- Chapter 13. Thermal Imaging and Deep Learning Object Detection Algorithms for Early Embryo Detection - A Methodology Development Addressed to Quail Precision Hatching -- Chapter 14. Intelligent Sensing and Robotic Picking of Kiwifruit in Orchard -- Chapter 15. Low-cost Automatic Machinery Development to Increase Timeliness and Efficiency of Operation for Small Scale Farmers to Achieve SDGs -- Chapter 16. Vision-based Leader Vehicle Trajectory Tracking for Multiple Agricultural Vehicles -- Chapter 17. Autonomous Robots in Orchard Management: Present status and future trends -- Chapter 18. Comparing Soil Moisture Retrieval from Water Cloud Model and Neural Network Using PALSAR-2 for Oil Palm Estates -- Chapter 19. Development of a Recognition System for Spraying Areas from Unmanned Aerial Vehicles Using a Machine Learning Approach -- Chapter 20. Basal Stem Rot Disease Classification by Machine Learning Using Thermal Images and an Imbalanced Data Approach -- Chapter 21. Early Detection of Plant Disease Infection using Hyperspectral Data and Machine Learning -- Chapter 22. The Spectrum of Autonomous Machinery Development to Increase Agricultural Productivity for Achieving Society 5.0 in Japan.

Konu Terimleri
Agriculture.
 
Machine learning.
 
Sustainability.

Yazar Ek Girişi
Ahamed, Tofael.

Tüzel Kişi Ek Girişi
SpringerLink (Online service)

Elektronik Erişim
https://doi.org/10.1007/978-981-19-8113-5


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