The Future of Agriculture.

Format:

Book

Author/Creator:

Pandey, Kavita.

Contributor:

Jain, Shikha.

Editor.

Language:

English

Subjects (All):

Sustainable agriculture.

Agricultural innovations.

Physical Description:

1 online resource (241 pages)

Edition:

1st ed.

Place of Publication:

Sharjah : Bentham Science Publishers, 2024.

Summary:

The Future of Agriculture: IoT, AI and Blockchain Technology for Sustainable Farming explores how cutting-edge technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and Blockchain are transforming farming for a sustainable future. Addressing challenges such as climate change, resource scarcity, and food supply chain inefficiencies, the book highlights how these technologies can improve decision-making, enhance crop yields, and increase transparency in agriculture. With a blend of theory and real-world applications, it covers everything from AI-driven pesticide prediction and disease identification to using Blockchain for efficient food supply chain management. This comprehensive guide is essential for researchers, professionals, and anyone interested in the intersection of technology and sustainable farming. Key Features:- Introduction to Digital Twin technology for sustainable farming- Practical applications of AI and IoT in agriculture- Blockchain's role in food supply chain management- Frameworks for precision agriculture and access to government schemes- Insights on integrating AI, IoT, and Blockchain into solid waste management systems Readership:Researchers (Academia, Ph.D. students), industry professionals, and trade experts.

Contents:

Cover

Title

Copyright

End User License Agreement

Contents

Foreword

Preface

List of Contributors

Digital Twin for Sustainable Farming: Developing User-Friendly Interfaces for Informed Decision-Making and Increased Profitability

Chandramohan Dhasarathan1,*, Ramachandra Reddy. B.2, Ashok Kumar. S.3 and Sambasivam Gnanasekaran4

INTRODUCTION

LITERATURE STUDY

PROPOSED METHODOLOGY- META-ANALYSIS

Digital Twin Technology in Agriculture

The Critical Benefit of Digital Twin Technology in Agriculture

OBSERVATION

DISCUSSIONS

RESEARCH HIGHLIGHTS AND FUTURE FOCUS

CONCLUSION

ACKNOWLEDGMENT

REFERENCES

Agricultural Resource Management Using Technologies Like AI, IoT, and Blockchain

Ashish Mahalle1,* and Snehlata Dongre1

AGRICULTURAL GROWTH IN INDIA

SUSTAINABLE AGRICULTURE METHODS

FRAMEWORK FOR AGRICULTURE DECISION SUPPORT

TECHNOLOGIES USED IN SMART FARMING

Internet of Things (IoT)

Artificial Intelligence (AI)

Blockchain

APPLICATIONS IN AGRICULTURE

ROLE OF ENGINEER IN DEVELOPING SMART FARMING

LIST OF ABBREVIATIONS

ACKNOWLEDGEMENT

Prediction for Increasing Yield Production with IoT and AI Using Soil Properties

Aravind H.S.1, Savitha Ambliihalli Chandrappa1,*, Neha Venkatesh2 and Kalyan Kumar Basavaiah3

Contributions of the Research Article

LITERATURE REVIEW

Wireless Sensor Network (WSN) /Internet of Things (IoT)

Data Analytics

FRAMEWORK OF THE PROPOSED SYSTEM

Components of Sub-modules

Arduino UNO

Machine Learning (ML)

Servo Motor

LCD Display

Sensors

Flowchart of the Proposed System

IMPLEMENTATION OF THE PROPOSED SYSTEM

RESULTS AND DISCUSSION

CONSENT FOR PUBLICATIONS

REFERENCES.

Pesticide Prediction and Disease Identification with AIoT

Ajay Kumar Dharmireddy1,*, Kambham Jacob Silva Lorraine1, Ravi Kumar Maddumala1 and Kotha Lavanya1

LITERATURE SURVEY

Different Techniques for Pest Detection

Image Processing in the Field of Agricultural Research

IOT-BASED SMART PEST DETECTION IN AGRICULTURE

Sensor Deployment

Pest Detection Sensors

Data Collection and Transmission

Data Analytics and Processing

Pest Detection and Alerts

Decision Support System

Integration with other Agricultural Systems

Historical Data Analysis and Prediction

Benefits of Smart Pest Detection in Agriculture using IoT Include

PROBLEM STATEMENT

EXISTING METHOD

Image Acquisition

Pre-processing

Feature extraction

Classification

PROPOSED MODEL

Proposed Methodology

Data Collection

Dataset Augmentation

Classification of Datasets

Deep Learning Model

STRUCTURE OF RESNET-18

Initial Layers

Basic Blocks (Residual Blocks)

Global Average Pooling and Classifier

Training and Testing the Model

Performance Evaluation

Components Used

Relay

RESULTS AND DISCUSSIONS

FUTURE WORK

Weed Control for Better Crop Health Using AIoT

Sanjana T.1,* and Madhusudhan K. N.1

SYSTEM FOR AUTONOMOUS ERADICATION OF WEEDS

Origin and History of AI, IoT and Blockchain Technology and their Pertinence in Food Supply Chain Management

Sudhanand Prasad Lal1,*, Abhinab Borah1, Sakshi Pundir1, Leezamoni Das1 and Diksha Srivastava1

METHODOLOGY

CHALLENGES OF AI IN SUPPLY CHAIN

Evolution and History of IoT

Applications of IoT

IoT in the Food Supply Chain

The architecture of IoT in the food supply chain.

Widely accepted definitions of Blockchain

Looking back at Blockchain

Characteristics of Blockchain

Application of Blockchain in Agriculture

Blockchain for Food Supply Chain Management

Any Food Supply Chain Starts with the following:

Genesis and History of Public Distribution System (PDS)

Evolution of PDS in India

Public Distribution System (PDS) in India

What is the current state of using modern ICT in the food sector?

What is SMART-PDS?

"Food for all Model" of Chhattisgarh

Centralized Online Real-Time Electronic Public Distribution System (CORE-PDS) of Chhattisgarh in India

Phases of Chhattisgarh's Model

CONCLUSION AND FUTURE PERSPECTIVES

Food Supply Chain Management by Leveraging AI, IoT, and Blockchain Technologies

K. Radhika1,*, Sheena Mohammed1, Satya Kiranmai Tadepalli1 and Kiranmaie Puvvula1

ARTIFICIAL INTELLIGENCE IN FOOD SUPPLY CHAIN MANAGEMENT

Role of AI in Food Supply Chain Management

Predictive Analytics for Demand Forecasting

AI-enabled Quality Control and Inspection

AI-enabled route optimization and logistics

LEVERAGING IOT IN FOOD SUPPLY CHAIN MANAGEMENT

Introduction to IoT in the Context of Food Supply Chain

IoT-enabled Smart Sensors for Real-time Monitoring

IoT-based Temperature and Humidity Control

BLOCKCHAIN TECHNOLOGY IN FOOD SUPPLY CHAIN MANAGEMENT

Role of Blockchain Technology in Food Supply Chain Management

Transparency and Traceability through Blockchain

Blockchain-based smart contracts for secure transactions

INTEGRATION OF AI, IOT, AND BLOCKCHAIN IN FOOD SUPPLY CHAIN MANAGEMENT

CHALLENGES AND RESEARCH DIRECTIONS

CONSENT FOR PUBLICATION

CONFLICT OF INTEREST

ACKNOWLEDGEMENTS

Framework Based on IoT, AI, and Blockchain for Smart Access to Government Agricultural Schemes

D. Vinodha1,*, M.J. Buvana2, S. Rajalakshmi2, J. Jenefa1, E.A. Mary Anita1 and Maria Lapina3

EXISTING SYSTEMS

TECHNOLOGIES USED

IoT in Precision Agriculture

Detectors of Soil Moisture

Weather Monitoring Sensor

Sensors for Crop Health

GPS Trackers

Drone

Role of AI in Precision Agriculture

Role of Blockchain in Precision Agriculture

Drone Monitoring System (DMS)

Soil Health Monitoring System

Crop Health Monitoring System

Health Assessing Model

Blockchains for Smart Access to Government Schemes

Blockchain for DMS (BC_DMS)

BC for Field-wise Sanctioned Schemes (BC_FSS)

Smart Contracts

ACKNOWLEDGMENTS

Transforming Agriculture with IoT for Precision Agriculture and Sustainable Crop Management

Suyash Bhardwaj1,*, Sasirekha Venkatesan2, Swati Rawat3 and Pashupati Nath4

INTRODUCTION TO IOT IN AGRICULTURE

Definition of IoT

Applications of IoT in Agriculture

Precision agriculture

Agricultural Drones

Automated irrigation

Livestock Monitoring

Crop Monitoring System

Smart Greenhouses

Environmental Monitoring

Remote Sensing

Supply Chain Management

Advantages of IoT-based agriculture systems

IOT SENSORS IN AGRICULTURE

Types of IoT sensors used in agriculture

Soil Moisture Sensors

Crop Sensors

Weather Sensors

Livestock Sensors

Irrigation Sensors

Sensor Technologies for Monitoring Crop Health

Optical Sensors

Spectral Sensors

Multispectral and Hyperspectral Imaging

Thermal Imaging

Drone-based Sensors

Soil Sensors

IOT-BASED DATA COLLECTION AND MANAGEMENT

Overview of Data Collection and Management Systems

Centralized Data Collection and Management Systems.

Decentralized Data Collection and Management Systems

Cloud-based Data Management Systems

Edge Computing in IoT-based Agriculture

IOT-BASED PRECISION AGRICULTURE

Definition of Precision Agriculture

Advantages of Precision Agriculture

Real-time Monitoring and Control using IoT in Precision Agriculture

Literature Review of IoT in Precision Agriculture

IOT-BASED SUSTAINABLE CROP MANAGEMENT

Crop Monitoring using IoT

Automated Irrigation Systems using IoT

Pest and Disease Management using IoT

Literature Review of Sustainable Crop Management

CHALLENGES AND FUTURE OF IOT FOR PRECISION AGRICULTURE AND SUSTAINABLE AGRICULTURE

Challenges for Precision Agriculture and Sustainable Agriculture

Technical Challenges in IoT-based Agriculture

Privacy and Security Concerns in IoT-based Agriculture

Future Trends in IoT-based Agriculture

Scientific Integrated Solid Waste Management System to Minimize Adverse Effects on Agriculture

Megha Jain1,* and Dhiraj Pandey1

RELATED STUDY

Stages in Remote Sensing

Resolution

Resolutions of Remote Sensing

Criteria for extracting the data

A. Data and Material

IMPLEMENTATION AND RESULTS

Simple Additive Weighting (SAW) Technique

Compromise Programming Technique

TOPSIS Technique

FUTURE SCOPE

FUNDING AGENCY

Subject Index

Back Cover.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

9789815274349

9815274341

OCLC:

1467875033