Preface

Agriculture is one of the oldest professions in the world for feeding the global population. Due to the growth of population and reduction in agricultural land, it is to be planned to move towards smart farming with the help of technology. Artificial Intelligence is playing a vital role in implementing smart methods for agriculture and it will change the aspects of performing agricultural activities. The objective of this book is to explore the applications of artificial intelligence in improving agricultural activities.

The book addresses several aspects of artificial intelligence applications in smart agriculture including, pest control, leaf disease identification, identification of weeds, field security, and applications of drones in smart farming.

A pest control and leaf disease identification system using machine learning technique is implemented where a novel algorithm is proposed, titled Black Window Optimization Algorithm with MayFly Optimization Algorithm (BWO-MA). Also, intelligent recognition and classification of Tomato Leaf Diseases using the Transfer Learning >Model are discussed. A pre-trained Squeeze Net Model is used to implement the Transfer Learning Model. Another leaf >disease detection system for Millet Leaves is elaborated on in the book. The proposed approach is implemented using Convolutional Neural Network.

Robots are important components in the implementation of smart farming and are playing a big role. A solar-powered robot for the identification of >weeds and damage in vegetables is developed and is one of the prime works published in the book. The proposed approach provides the capability for effective control >of weeds and >damage to crops and also assists in harvesting.

Apart from machine learning and robotics systems, the Internet of Things (IoT) systems are also playing a vital role in the implementation of smart farming and precision agriculture. An IoT-based system powered with AI classification technique is developed for the security >of the field and it is mentioned and explained in the book.

Weather conditions are very important for the agricultural system. The prediction of weather conditions will play a big role in planning agricultural activities and dealing with adverse weather conditions. A weather forecasting system for smart farming is also developed using machine learning techniques.

The book also addresses the role of artificial intelligence and drones in smart farming along with the introduction of precision farming, intelligent crop planning and climate smart agriculture.

We hope that the book will surely help the >people working in the area of smart agriculture and precision agriculture as it addresses many real-world problems of the agriculture sector through machine learning, IoT, deep learning, etc.