Introduction
Agriculture is rapidly evolving with smart technologies that make farming more efficient, secure, and sustainable. Smart Technologies for Next-Generation Agriculture breaks down how Deep Learning, IoT, and Blockchain are revolutionising crop care, livestock husbandry, yield prediction, and farm security through applied research and real-world use cases.
The book also highlights challenges like data safety, environmental risks, and ethical concerns while exploring emerging frontiers such as nanotechnology and AI-driven disease detection in key crops.
Key Features
- - Detect crop diseases using deep learning and ensemble models.
- - Optimise yield prediction using big data analytics.
- - Empower livestock monitoring using IoT sensors.
- - Strengthen animal welfare with smart husbandry systems.
- - Enable farm traceability using blockchain networks.
- - Secure agricultural IoT systems with AI-based cybersecurity.
- - Improve precision farming using device-to-device communication.
Target Readership:
Researchers, agriculture technologists, and farm innovators; also valuable for postgraduate students and policymakers exploring sustainable digital agriculture solutions.