Название: Artificial Intelligence for Precision Agriculture
Автор: Pethuru Raj, N. Gayathri, G. Jaspher Willsie Kathrine
Издательство: CRC Press
Год: 2025
Страниц: 322
Язык: английский
Формат: pdf (true), epub
Размер: 25.5 MB
Precision agriculture is a next-generation farming management concept that optimizes resource use, productivity, quality, profitability, and sustainability by observing and responding to crop variability. Precision agriculture employs digital technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), 5G communication, cybersecurity, edge computing, cloud-native principles, and blockchain to ensure crops and soil receive exactly what they need for optimal health and productivity. Artificial Intelligence for Precision Agriculture explores the latest developments in precision agriculture, detailing how AI contributes to its goals. The book discusses how precision agriculture solutions use IoT devices, data storage, AI analytics, connectivity, and cloud infrastructures to analyze factors such as soil type, terrain, weather, plant growth, and yield data. It also examines edge technologies—sensors, microchips, beacons, RFID tags, robots, drones, and actuators—that collect field data and transmit it to cloud-based AI platforms for analysis. The book shows how AI-driven insights guide actions in the field, such as crop rotation, optimal planting and harvesting times, and soil management, and help farmers apply the right amounts of water, fertilizers, and pesticides, reducing waste and environmental impact. Machine Learning is a technique that uses mathematics and statistical learning to create a model that helps in predicting the values which are not known prior. In Machine Learning, we try to solve problems with computers without explicitly programming them for a specific task.
Автор: Pethuru Raj, N. Gayathri, G. Jaspher Willsie Kathrine
Издательство: CRC Press
Год: 2025
Страниц: 322
Язык: английский
Формат: pdf (true), epub
Размер: 25.5 MB
Precision agriculture is a next-generation farming management concept that optimizes resource use, productivity, quality, profitability, and sustainability by observing and responding to crop variability. Precision agriculture employs digital technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), 5G communication, cybersecurity, edge computing, cloud-native principles, and blockchain to ensure crops and soil receive exactly what they need for optimal health and productivity. Artificial Intelligence for Precision Agriculture explores the latest developments in precision agriculture, detailing how AI contributes to its goals. The book discusses how precision agriculture solutions use IoT devices, data storage, AI analytics, connectivity, and cloud infrastructures to analyze factors such as soil type, terrain, weather, plant growth, and yield data. It also examines edge technologies—sensors, microchips, beacons, RFID tags, robots, drones, and actuators—that collect field data and transmit it to cloud-based AI platforms for analysis. The book shows how AI-driven insights guide actions in the field, such as crop rotation, optimal planting and harvesting times, and soil management, and help farmers apply the right amounts of water, fertilizers, and pesticides, reducing waste and environmental impact. Machine Learning is a technique that uses mathematics and statistical learning to create a model that helps in predicting the values which are not known prior. In Machine Learning, we try to solve problems with computers without explicitly programming them for a specific task.