IoT and AI in Agriculture (eBook)
493 Seiten
Springer Nature Singapore (Verlag)
978-981-97-1263-2 (ISBN)
This book covers smart agricultural space and its further development with an emphasis on ultra-saving labor shortages using AI-based technologies. A transboundary approach, as well as artificial intelligence (AI) and big data for bioinformatics, are required to increase timeliness and supplement the labor shortages, ensure the safety of intangible labor migration system to achieve one of the sustainable development goals (SDG) to secure food security (Society 5.0, SDG 1 and 2). With this in mind, the book focuses on the solution through smart Internet of Things (IoT) and AI-based agriculture, such as automation navigation, insect infestation, and decreasing agricultural inputs such as water and fertilizer, to maintain food security while ensuring environmental sustainability. Readers will gain a solid foundation for developing new knowledge through the in-depth research and education orientation of the book on how the deployment of outdoor and indoor sensors, AI/machine learning (ML), and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms is nurturing and driving the pace of smart agriculture outdoor and indoors at this current time. Furthermore, the book introduces the smart system for automation challenges that are important for an unmanned system for considering safety and security points. The book is designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science. The greatest care has been made to deliver a diverse range of resource areas, as well as enormous insights into the significance and scope of IoT, AI, and ML in the development of intelligent digital farming and smart agriculture, providing comprehensive information to the intended readers.
This book covers smart agricultural space and its further development with an emphasis on ultra-saving labor shortages using AI-based technologies. A transboundary approach, as well as artificial intelligence (AI) and big data for bioinformatics, are required to increase timeliness and supplement the labor shortages, ensure the safety of intangible labor migration system to achieve one of the sustainable development goals (SDG) to secure food security (Society 5.0, SDG 1 and 2). With this in mind, the book focuses on the solution through smart Internet of Things (IoT) and AI-based agriculture, such as automation navigation, insect infestation, and decreasing agricultural inputs such as water and fertilizer, to maintain food security while ensuring environmental sustainability. Readers will gain a solid foundation for developing new knowledge through the in-depth research and education orientation of the book on how the deployment of outdoor and indoor sensors, AI/machine learning (ML), and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms is nurturing and driving the pace of smart agriculture outdoor and indoors at this current time. Furthermore, the book introduces the smart system for automation challenges that are important for an unmanned system for considering safety and security points. The book is designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science. The greatest care has been made to deliver a diverse range of resource areas, as well as enormous insights into the significance and scope of IoT, AI, and ML in the development of intelligent digital farming and smart agriculture, providing comprehensive information to the intended readers.
| Erscheint lt. Verlag | 1.7.2024 |
|---|---|
| Zusatzinfo | XXIV, 493 p. 310 illus., 278 illus. in color. |
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Informatik ► Weitere Themen ► Hardware | |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| Naturwissenschaften ► Biologie ► Botanik | |
| Naturwissenschaften ► Biologie ► Ökologie / Naturschutz | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Umwelttechnik / Biotechnologie | |
| Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei | |
| Schlagworte | Data driven system in agriculture • Deep learning • Digital Agriculture • SDG 1 • SDG 2 • Smart Agriculture • Smart horticultural crop management |
| ISBN-10 | 981-97-1263-7 / 9819712637 |
| ISBN-13 | 978-981-97-1263-2 / 9789819712632 |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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