Agriculture 5.0

Artificial Intelligence, IoT and Machine Learning

Latief Ahmad, Firasath Nabi

• Publisher: CRC Press
• Year: 2021
• Print ISBN: 9780367646080
• eBook ISBN: 9781000364439
• Topic: Ciencias biológicas
• Subtopic: Ética empresarial

Agriculture 5.0: Artificial Intelligence, IoT & Machine Learning provides an interdisciplinary, integrative overview of latest development in the domain of smart farming. It shows how the traditional farming practices are being enhanced and modified by automation and introduction of modern scalable technological solutions that cut down on risks, enhance sustainability, and deliver predictive decisions to the grower, in order to make agriculture more productive. An elaborative approach has been used to highlight the applicability and adoption of key technologies and techniques such WSN, IoT, AI and ML in agronomic activities ranging from collection of information, analysing and drawing meaningful insights from the information which is more accurate, timely and reliable.It synthesizes interdisciplinary theory, concepts, definitions, models and findings involved in complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership.

This book clarifies hoe the birth of smart and intelligent agriculture is being nurtured and driven by the deployment of tiny sensors or AI/ML enabled UAV's or low powered Internet of Things setups for the sensing, monitoring, collection, processing and storing of the information over the cloud platforms. This book is ideal for researchers, academics, post-graduate students and practitioners of agricultural universities, who want to embrace new agricultural technologies for Determination of site-specific crop requirements, future farming strategies related to controlling of chemical sprays, yield, price assessments with the help of AI/ML driven intelligent decision support systems and use of agri-robots for sowing and harvesting. The book will be covering and exploring the applications and some case studies of each technology, that have heavily made impact as grand successes. The main aim of the book is to give the readers immense insights into the impact and scope of WSN, IoT, AI and ML in the growth of intelligent digital farming and Agriculture revolution 5.0.The book also focuses on feasibility of precision farming and the problems faced during adoption of precision farming techniques, its potential in India and various policy measures taken all over the world. The reader can find a description of different decision support tools like crop simulation models, their types, and application in PA.

Features:

• Detailed description of the latest tools and technologies available for the Agriculture 5.0.

• Elaborative information for different type of hardware, platforms and machine learning techniques for use in smart farming.

• Elucidates various types of predictive modeling techniques available for intelligent and accurate agricultural decision making from real time collected information for site specific precision farming.

• Information about different type of regulations and policies made by all over the world for the motivation farmers and innovators to invest and adopt the AI and ML enabled tools and farming systems for sustainable production.

1	Introduction to Precision Agriculture

1.1 History of Precision Agriculture and Its Global Adoption

Precision farming was adopted by US agriculture in the 1980s at a sluggish rate of 10 to 15 years due to doubt in profitability at that time, as no legitimate pieces of evidence were present and the adoption of this innovation was uneconomical. Some specific reasons include the lack of genuine information at that time, farmer attitude, economic constraints in acquiring technology, and the technology itself. Later, it was discovered that the two major reasons were:

I. Willingness:
Willingness is directly proportional to the availability of information about PA, precision in information, and the probability of positive results.

II. Ability to Adopt:

Early in the year 2000, it was identified that the adoption of precision farming was related to:

a. The degree of relevance between the existing problem and the technology

b. Ease of handling the technology

c. Most importantly, the profit related to the aforementioned adoption

During the early stages of implementing precision farming, improving efficiency was the only motivating factor and, of course, this was not sufficient. Batte and Arnholt investigated that profit that was related to PA was the biggest contributing factor [1]. During the first ten years, the 21st-century exponential rate for acceptance of PA was observed among producers as well as commercial businesses.

The reason for this rapid growth in adoption during the last 15 years is related to certain factors:

1. In terms of efficiency, productivity, and profitability executed in an eco-friendly manner, nutrient management research has enabled development.

2. The affordable pricing of commodities led to high net profits and large investments in advanced technologies.

3. Auto-guidance systems not only improved the farming efficiencies but also reduced the manual efforts of farmers.

4. There was an increase in the number of skilled people who had knowledge about both agricultural and technological domains.

The abovementioned factors only constitute a few of the reasons for the adoption of PA in the past 15 years. However, there was a gap that needs to be bridged among different sectors. The acceptance of PA has boosted due to the collaborative and synchronized efforts of industries, researchers, institutions, and the media. Global extensive research is proving beneficial and is significantly changing the agricultural domain [2].

1.2 Precision Agriculture – Introduction

This book is aimed to provide a deeper insight into precision agriculture by discussing almost all of the techniques and tools that are currently used all over the world.

India is a vast land with a diverse climate and has an edge in producing a multitude of vegetables and crops throughout the year. According to the Ministry of Agriculture, India has achieved the second position in terms of the production of fruits and vegetables worldwide, following China (Reported by Horticulture at a Glance 2015). The Indian population is completely dependent on the production of cereal crops, fruits, vegetables, and milk, thus turning the country into a farming powerhouse globally. Nonetheless, we are still lacking in terms of productivity, focus, competition, and zoned agricultural sector. The requirement to remove these limits is quite simple: we need to adopt and promote the use of new technology and sciences that will be achieved by rigorous research in the field of agriculture [3]. The dearth of awareness as well as inadequate utilization of technology and traditional mechanisms for handling agricultural practices and constraints have negatively affected production all over the country.

The introduction of the latest and most innovative techniques, concepts, methodologies, and technology to replace conventional agricultural ways, thus making it sustainable is called Precision Agriculture (PA). It is focused on maximizing production while using the least amount of resources while causing minimum impact on the environment by judicious irrigation and an adequate quantity of pesticides and fertilizers. PA critically depends upon factors such as information, technology, and management which have equal importance and accords numerous benefits on crops [4]. Nowadays, we become increasingly familiar with the term, and there has been a progressing trend toward this field. When agricultural practices are executed rather efficiently, such as when the proper amount of materials required (e.g. fertilizers, pesticides, nutrients, water, etc.) are supplied at the proper location and at the correct time to boost production, to grow profits, to directly promote soil health, and to indirectly increase water quality and farmer health while reducing environmental wastes is termed as precision agriculture [5]. In India, PA is still in its infancy, and significant work is currently proceeding in this field.

1.2.1 Foreign Perspective

The first definition of PA was given by the US House of Representatives (US House of Representatives, 1997) [6].

Precision agriculture is an integrated information- and production-based farming system that is designed to increase long-term, site-specific, and whole farm production efficiency, productivity, and profitability while minimizing unintended impacts on wildlife and the environment.

According to Gandonou [7]:

PA can be defined as a set of technologies that have helped propel agriculture into the computerized information-based world and is designed to help farmers get greater control over the management of farm operations.

As reported by the Second International Conference on Site-Specific Management for Agricultural Systems that was held in Minneapolis, Minnesota, in March 1994 [6]:

The precision farming system within a field is also referred to as site-specific crop management (SSCM).

As stated by the National Research Council, Italy 1997 [6]:

SSCM refers to a developing agricultural management system that promotes variable management practices within a field according to site or soil conditions.

The genetic improvement, agrochemical practices, irrigation, and farm machinery have been successful in improving productivity, but this is not significant enough to meet the continuously growing demand due to population expansion. Increased demand poses a threat to the environment as well as food security all over the world. Numerous innovative attempts have been pursued to enable sustainable crop production. Precision farming system (PFS) was one of the efforts that were undertaken during the early 1990s. This made its appearance in various forms, depending on the knowledge and technology that were available during its time. PFS was the combination of the latest technology and the mechanization of the agro-sector. PFS made a sharp turn with the introduction of electronic information technology which enabled the collection, processing, and analysis of the data from different sources streamlined for decision-making. PFS has gained the platform due to a decline in the rates of agricultural products and increased production. Even the National Aeronautics and Space Administration (NASA) has shown interest in PA, hence proving the importance of its enactment [6]. Furthermore, precision farming technology (PFT) acts as a reliable base for making site-specific management (SSM) decisions. There has been an enormous demand for information about technologies that are used to manage agricultural production systems with the introduction of:

1. Yield monitors

2. Global positioning systems

3. Improvements in computing power and data management [8].

This emphasizes the use of technologically sophisticated equipment and promotes research and development in agronomy and crop and soil science in providing vital information and supporting decision-making for variable application of inputs at the local levels too [9].

1.2.2 Indian Perspective

Below is a definition of PA that is accepted in India:

Precision agriculture, satellite farming, or site-specific crop management is farming based on observing, measuring, and responding to inter- and intra-field variability in crops.

Another interpretation is the following:

PA is an information- and technology-based farm management system to identify, analyze, and manage variability within fields for optimum profitability, sustainability, and protection of land resources.

The succeeding meaning also defines PA:

PA is the precision application of technologies and input based on soil, crop weather, and market de...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Contents
• Authors
• List of Abbreviations
• Chapter 1 Introduction to Precision Agriculture
• Chapter 2 Smart Intelligent Precision Agriculture
• Chapter 3 Adoption of Wireless Sensor Network (WSN) in Smart Precision Agriculture
• Chapter 4 IoT (Internet of Things) Based Agricultural Systems
• Chapter 5 AI (Artificial Intelligence) Driven Smart Agriculture
• Chapter 6 Machine Learning (ML) Driven Agriculture
• Chapter 7 Data-Driven Smart Farming
• Chapter 8 Decision-Making and Decision-Support Systems
• Chapter 9 Agriculture 5.0 – The Future
• Chapter 10 Social and Economic Impacts
• Chapter 11 Environmental Impact and Regulations
• Index