TOPICS OF INTEREST
The topics covered in the edited book will include, but not limited to:

Part 1: Fundamentals of Smart Agriculture

Topic 1. Machine learning based Agriculture

Role of machine learning in agriculture

Component of machine learning

Basic of predictions

Water level management

Topic 2: Monitoring agriculture essentials

Soil monitoring and management

Daily dew point temperature

Soil drying

Crop quality prediction

Yield prediction

Weed detection methods

Topic 3: Livestock management in agriculture

Livestock production

Animal welfare

Machine learning technique for livestock management

Animal weed management methods

Part 2: Market, Technology and products

Topic 4: Agriculture Economics

Prediction of Crop price

Impact of GDP

Economical changes in Traditional Agriculture Vs Machine Learning Agriculture

Meteorology

Topic 5: Digital Marketing and its impact

Connection with Local Market using Android App

Daily marketing Price prediction

Direct selling price in small vendors market

Future price prediction of crop

Topic 6: Technology and products

Harvesting crops products and technologies

Field work management technologies

Human Resource Management

Blue River Technology–Weed Control

Part 3: Tools and Techniques

Topic 7: Modeling Techniques used in Smart Agriculture

Fuzzy logic

Artificial neural networks (ANN)

Neuro-fuzzy logic

Expert systems

Deep Learning approaches

Topic 8: Diseases detection

Different diseases detection method

Using Machine Learning for Image-Based Plant Disease Detection

Convolutional Neural Network (CNN) for diseases detection

Automatic detection of diseases in leaves, neural networks application

Topic 9: Food Security

Care Behavior

Health Care

Goods Effecting Food Security

Private/Public transfers

Topic 10: Medicines Care Management

Education and Training as Intervention Strategies

The Agricultural Environment

Occupational and Environmental Health for the Health Professions

Agricultural Medicine: A Practical approach

Topic 11: Detection and diagnosis of plant diseases

Detection and diagnosis diseases

Current and Prospective Methods for Plant Disease Detection

Relationship Between Agriculture and Healthcare

Virus in the infected plant material

Topic 12: Machine Learning Technique for agriculture image recognition

Application of Image Processing in Agriculture

Use of Different Technologies of Image Recognition in Agriculture

Image sharpening and restoration

Image Retrieval