IoT and AI in Agriculture
Springer Verlag, Singapore
978-981-95-5217-7 (ISBN)
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The intersection of AI, IoT, and agriculture is a critical focus in the current era, where food security, climate change, and sustainability are top global priorities. With the agricultural sector facing unprecedented challenges due to changing climate conditions, the integration of advanced technologies offers a pathway to resilience and sustainability. This book is timely as it addresses the urgent need for innovation in agriculture, providing actionable strategies to help farmers and agricultural managers navigate the complexities of modern farming while safeguarding the environment. This publication is particularly important now, as it contributes to the broader discourse on how technology can support sustainable development goals and ensure a stable food supply for the growing global population.
Tofael Ahamed is an Associate Professor from Institute of Life and Environmental Sciences, University of Tsukuba, Japan. He performs research in the field of precision agriculture technology, agricultural robotics and decision support systems. Tofael focuses on the holistic approach of smart application using Internet of Things (IoT) and Artificial Intelligence (AI) in agriculture, where crop, orchard and livestock production varies spatially and temporally within the field boundaries depending on the soil, nutrient, and environmental conditions. Tofael is a member of American Society of Agricultural and Biological Engineers (ASABE), Japanese Society of Agricultural Machinery and Food Engineers (JSAM), Japanese Society of Agricultural Information (JSAI) and Japan Section of Regional Science Association (JSRSAI). He is also serving as one of the Associate Editors for Computer and Electronics in Agriculture (Elsevier), Agricultural Information Research (JSAI), Editorial Member for Asia-Pacific Journal of Regional Science (Springer-Nature).
Chapter 1. High-Throughput Field Plant Phenotyping of Horticultural Crops.- Chapter 2. Development of a Raspberry Pi-Based Automated Primary Root Length Measurement System for Tomato (Solanum lycopersicum).- Chapter 3. Development of Smart Drip Irrigation and Fungicide Application System for the Grapevine Management.- Chapter 4. Challenges and Opportunities for Developing Mini-plant Factory for Vegetable Cultivation in Household Urban Farming.- Chapter 5. Computational Intelligence in Climate-Adaptive Agriculture: Pathways to Resilient Food Systems.- Chapter 6. Agronomic Performance and Physiological Responses of Inbred Rice (Rc 512) Using Drone Seeding Technology.- Chapter 7. Deep Learning Strategies for Smart Agricultural Space - Diagnostics, Automation, and Quality Systems.- Chapter 8. Feature Selection Technique for Model Development.- Chapter 9. Development of Remote Autonomy of Multi-Cluster Agricultural Machinery Control System Using YOLO Deep Learning Algorithm and WebSocket Protocol.- Chapter 10. Development of Navigation System in Rural Roads using Deep Learning Algorithm for Autonomous Crawler Tractor.- Chapter 11. Development of Orchard Autonomous System using Zigbee Communication and Visual SLAM Technology.- Chapter 12. Instance Segmentation Based on Deep Learning Algorithm for Autonomous Navigation in Orchards.- Chapter 13. Intelligent Recognition of Orchard Environment: Instance Segmentation of Trees and Roads.- Chapter 14. Strategic Short Note: Prospect of Small-scale Agricultural Mechanization for Sustainable Agriculture in a Climate Change Context.- Chapter 15. A Review- Smaller degree multi- arm robotic systems for fruit harvesting.- Chapter 16. Development of Small-Scale Automatic Seed and Fertilizer Broadcasting Machinery.- Chapter 17. Design and Fabrication of Autonomous Weeder for Agriculture Fields.- Chapter 18. Weeding Technologies in Tropical Places for Cassava Plantations.- Chapter 19. AI Agent System for Agricultural Water Resources Management.- Chapter 20. An IoT Assisted Dual Supply Solar Food Drying System for Tropical Agricultural Conditions.- Chapter 21. Technological Transitions in Thermal Drying: Integrating Microwave and Heat Pump Technologies with AI and IoT to Enhance Productivity in Food and Agricultural Systems.- Chapter 22. Prospects on the Horizon: Analyzing the Impacts of Deep Learning and Machine Vision in Quail Farming.- Chapter 23. AI and IoT to Integrate Automation in Farm Management: A Path to Sustainable Agriculture in Changing Climates.
| Erscheint lt. Verlag | 15.2.2026 |
|---|---|
| Zusatzinfo | 157 Illustrations, color; 15 Illustrations, black and white |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Netzwerke |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei | |
| Schlagworte | canopy management • Data Driven System and AI in Agriculture • Deep learning • Digital Agriculture • orchard management • Pest and diseases management • Smart horticultural crop management • weed management |
| ISBN-10 | 981-95-5217-6 / 9819552176 |
| ISBN-13 | 978-981-95-5217-7 / 9789819552177 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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