Preface
Page: ii-iii (2)
Author: Kavita Pandey, Shikha Jain, Dhiraj Pandey and Omprakash Kaiwartya
DOI: 10.2174/9789815274349124010002
Digital Twin for Sustainable Farming: Developing User-Friendly Interfaces for Informed DecisionMaking and Increased Profitability
Page: 1-20 (20)
Author: Chandramohan Dhasarathan*, Ramachandra Reddy. B., Ashok Kumar. S. and Sambasivam Gnanasekaran
DOI: 10.2174/9789815274349124010004
PDF Price: $15
Abstract
This chapter endeavors to develop a robust digital model for farm
optimization with the primary objectives of enhancing resource utilization, minimizing
waste, and increasing productivity while mitigating environmental impact. The
proposed digital twin will leverage data from diverse sources, including sensors,
weather data, soil moisture levels, and crop yields. Methodologically, the integration
and processing of this varied data will be achieved through advanced algorithms,
ensuring a comprehensive and accurate representation of the farm. The simulation
aspect of the digital twin will explore different scenarios, allowing for a nuanced
understanding of the impact of interventions on farm productivity and sustainability.
Specific scenarios, such as testing the effects of varied irrigation strategies on crop
yields or optimizing fertilizer inputs, will be explored. Methodological considerations
will be discussed, addressing challenges related to data integration, format disparities,
and accuracy variations across different data sources. Crucially, collaboration with
farmers and stakeholders will be a cornerstone of this research. Their insights and realworld experiences will be actively incorporated throughout the development process,
ensuring that the digital twin is tailored to the practical needs and challenges faced in
agricultural operations. In tandem with this, the development of user-friendly interfaces
will be emphasized, providing farmers and stakeholders with accessible tools for
interacting with the digital twin. Specific functionalities, tailored to inform periodic
decisions and processes, will be integrated into the interfaces, fostering usability and adoption. The chapter will examine the assessment of environmental impact. A detailed
examination of the criteria and indicators used to measure and minimize the farm's
environmental footprint will be discussed. By addressing these methodological
considerations comprehensively, this research aims to not only optimize resource use
and reduce waste but also contribute to the transformative advancement of sustainable
and efficient farming practices.
Agricultural Resource Management Using Technologies Like AI, IoT, and Blockchain
Page: 21-39 (19)
Author: Ashish Mahalle* and Snehlata Dongre
DOI: 10.2174/9789815274349124010005
PDF Price: $15
Abstract
The future of farming and farmers in India is smart farming, which uses
intelligence to integrate information technology and communication tools equipped
with sensors and actuators for embedded farm management. This involves using
emerging technologies like AI, IoT, and blockchain to employ robots, drones, and
artificial intelligence in the agricultural sector, which is modifying traditional farming
practices and simultaneously posing a variety of difficulties. The aim is to explore the
various tools and equipment used. Pesticides are an essential material used in
agricultural land to eliminate insects or other harmful organisms that affect crop yields.
However, excessive use of pesticides can result in problems such as decreased soil
fertility and an increase in insect species' immunity. To overcome these challenges, a
land-specific variable-rate spraying and directional spraying method can be employed,
which offers an accurate and flexible alternative strategy. Soil moisture is a crucial
parameter in agriculture as it affects plant growth and survival. Various factors like air
content, salinity, toxic substances, soil structure, temperature, and heat capacity of the
ground can affect soil moisture. Agriculture resource management can be enhanced by
designing various technologies like AI, IoT, and blockchain by using IoT sensors,
drones and satellites, AI-powered cameras, weather stations, crop yield predictions,
disease and pest detection, crop optimization, supply chain transparency, resource
optimization, online communities, and data sharing networks. AI optimizes resource
allocation and predicts outcomes. IoT provides real-time data for precision farming and
livestock monitoring, while blockchain ensures transparency and security in supply
chains and transactions, revolutionizing agricultural resource management. Agriculture
resource management using technologies like AI, IoT, and blockchain comes with
ample potential results like increasing efficiency in agricultural operations, enhancing
productivity, improving crop and livestock health, and facilitating knowledge sharing
and collaboration.
Prediction for Increasing Yield Production with IoT and AI Using Soil Properties
Page: 40-61 (22)
Author: Aravind H. S., Savitha Ambliihalli Chandrappa*, Neha Venkatesh and Kalyan Kumar Basavaiah
DOI: 10.2174/9789815274349124010006
PDF Price: $15
Abstract
'Wireless Sensor Networks and 'The Internet of Things' are the two
imminent commonalities in agricultural science that allow the development of less
exclusive systems to install, control, and maintain low-power standard protocols. The
work makes use of low-cost sensors and IoT platforms to help farmers improve
agricultural systems with better yield and reduce insufficient usage of water. Precision
agriculture helps in terms of quality of yield, efficiency of product, decrease in the
environmental harness, and minimal usage of natural assets. The proposed precision
model obtains raw properties of the given soil and achieves an overall accuracy of
93.33% in predicting the ideal crop that can be cultivated for the given soil sample
using the KNN algorithm and develops a continuous crop monitoring system for the
expected crop based on the predefined crop properties.
Pesticide Prediction and Disease Identification with AIoT
Page: 62-85 (24)
Author: Ajay Kumar Dharmireddy*, Kambham Jacob Silva Lorraine, Ravi Kumar Maddumala and Kotha Lavanya
DOI: 10.2174/9789815274349124010007
PDF Price: $15
Abstract
Agriculture is vital to human survival and has a significant impact on the
economy of any nation. Crop protection costs millions of dollars per year. Insects and
other pests pose a serious threat to the health of a harvest. Excessive use of chemical
fertilizers and pesticides negatively affects the crop and soil quality. Therefore, one
way to safeguard the harvest and mitigate potential losses is through early
identification of the pests. Examining the crop at the right moment is the best technique
to determine its overall health. While manual inspection is the standard way of
conducting field inspection, it becomes challenging for large fields. In addition, manual
inspection would be exceedingly expensive and tedious. To address this, an automated
system is needed to detect pests, identify them, and recommend appropriate fertilizers
using an IoT system. Therefore, automated pest detection has become a major focus for
researchers globally, as it offers a more efficient and cost-effective alternative to
manual inspection. In this work, a smart agriculture system has been proposed that
monitors crops, identifies pests, and allows remote control. The dataset comprises over
4000 images of corn leaves, categorized into rust, blight, grey spots, and healthy
leaves. By employing Convolutional Neural Networks (CNN), the system has achieved
a remarkable 99% accuracy in pest detection.
Weed Control for Better Crop Health Using AIoT
Page: 86-99 (14)
Author: Sanjana T.* and Madhusudhan K. N.
DOI: 10.2174/9789815274349124010008
PDF Price: $15
Abstract
Agriculture is one of the major sources of economy in India. Quality of
crops and optimal yield are possible amidst several challenges, such as climate change,
water scarcity, and weeds, by means of sustainable agriculture. Modern science and
technological advancements can be used to address these challenges and, hence,
maximize agricultural productivity.
This chapter focuses on weed control using a combination of computer vision and IoT.
Weed is an unwanted crop that affects the growth of the actual crop by absorbing soil
nutrients, water, and sunlight. It is extremely important to remove the weeds. Targeted
spraying to kill the weed has been the most effective solution. Such a system is costeffective and time-saving for large farms. The major concern in this method is the
identification of the weed. There are several types of weeds, and identifying them
among the actual crop is critical. False identification may lead to large economic
losses. An efficient product for weed removal can be designed by combining the
knowledge of IoT, image processing, and artificial intelligence (AI). AI and image
processing aid in identifying and classifying the weeds. AI also helps in analyzing the
risk of weed and the ineffective usage of weed killer, along with the amount of
pesticide to be sprayed based on the type of weed. This chapter discusses sustainable
agriculture, works carried out in the field of smart farming, the significance of
technologies such as IoT and AI, and the design of a weed killer bot, which mainly
uses image processing.
Origin and History of AI, IoT and Blockchain Technology and their Pertinence in Food Supply Chain Management
Page: 100-118 (19)
Author: Sudhanand Prasad Lal*, Abhinab Borah, Sakshi Pundir, Leezamoni Das and Diksha Srivastava
DOI: 10.2174/9789815274349124010009
PDF Price: $15
Abstract
In a world where hunger and malnourishment are still a matter of concern,
food loss, wastage, and its timely availability must be addressed immediately. Based on
an extensive literature review and secondary data, this manuscript has tried to come up
with holistic, contemporary solutions for food supply chain management. Against this
backdrop, tools viz., IoT, AI, and blockchain will not only manage food loss, wastage,
and timely availability but also revamp transparency, food quality and safety. IoT
architecture offers tracking solutions through measurement, network, service, and
application layers using various sensors and WiFi-connected devices. Artificial
Intelligence (AI) and the Internet of Things are becoming significant facilitators of
supply chain management (SCM) optimization. The adoption of AI technology has
been associated with a 15% reduction in logistics costs, a 35% reduction in inventory
levels, and a 65% increase in customer service levels. It assists in demand forecasting,
enhanced safety, cost saving, boosting revenue, and chiefly on-time delivery. Block
Chain Technology (BCT) system can be programmed to record and track food supply
chain transactions. Chhattisgarh in India has developed the Centralized Online RealTime Electronic Public Distribution System (CORE-PDS) and has become a model
state in the ‘Public Distribution System (PDS)’. Unfortunately, Chhattisgarh’s model
fell prey to scams viz., bogus ration cards, irregularities in rice stock, and poor quality
rice and salt samples collected, which were unsuitable for human consumption because
of no mid-term audit and monitoring. The chapter concludes that all these anomalies
would not have happened to such an extent or have been addressed timely if the
technological trinity viz., IoT, AI, and Blockchain, had been incorporated judiciously
into the PDS system.
Food Supply Chain Management by Leveraging AI, IoT, and Blockchain Technologies
Page: 119-141 (23)
Author: K. Radhika*, Sheena Mohammed, Satya Kiranmai Tadepalli and Kiranmaie Puvvula
DOI: 10.2174/9789815274349124010010
PDF Price: $15
Abstract
Traceability is an important component of food supply chain management
because it allows businesses to track food products from their origin to the point of
consumption. However, the current food supply chain system frequently lacks proper
traceability methods, making it difficult to pinpoint the source of food safety concerns,
monitor product quality, and assure regulatory compliance. As a result, there is a
growing need to rethink food supply chain management to assure traceability. Artificial
intelligence (AI), the Internet of Things (IoT), and blockchain are contributing to the
resolution of these issues by increasing accountability, traceability, and efficiency. The
application of blockchain, IoT, and AI to food supply chain management is examined
in this book chapter. It highlights the possible advantages of incorporating these
technologies into the food industry, including improved food safety, real-time food
quality monitoring, and increased supply chain visibility. It looks at other uses as well,
such as decentralized food traceability systems, smart packaging, and predictive
analytics. The chapter also discusses the obstacles and restrictions that come with
implementing these technologies in the food supply chain, as well as potential solutions
and effectiveness.
Framework Based on IoT, AI, and Blockchain for Smart Access to Government Agricultural Schemes
Page: 142-163 (22)
Author: D. Vinodha*, M. J. Buvana, S. Rajalakshmi, J. Jenefa, E. A. Mary Anita and Maria Lapina
DOI: 10.2174/9789815274349124010011
PDF Price: $15
Abstract
Agriculture plays an important part in most countries, such as India. A
survey says that 54.6% of the total labor force of India is engaged in agriculture and its
connected activities. The government is announcing many schemes to facilitate
agriculture and support farmers. But most of the farmers are from poor families and are
not able to reach the government schemes when they are really in need. Also, it is
required to observe and measure the inter and intra-field variability in crops to enjoy
the complete benefits of government schemes. This can be done with the advancements
in the field of the Internet of Things. Information related to the impact of natural
calamities on the agricultural field, malfunctions in the machinery used for cropping,
yielding level, and health status of crops can be measured using the technology of IoT
(Internet of Things) and analyzed using AI (Artificial Intelligence). Blockchain plays a
critical role in replacing traditional means of data storage and exchanging agricultural
data with a more trustworthy, immutable, transparent, and decentralized approach. By
keeping all the transactions related to government schemes in blockchain, the possible
crimes in the form of false data by the intermediate dealers acting between the farmers
and the government can be addressed. This, in turn, allows useful government schemes
to reach the farmer in time. We propose to develop a theoretical model using IoT, AI,
and blockchain, which can assist the farmers in benefitting from the appropriate
schemes announced by the government in time and achieving precise agriculture.
Transforming Agriculture with IoT for Precision Agriculture and Sustainable Crop Management
Page: 164-200 (37)
Author: Suyash Bhardwaj*, Sasirekha Venkatesan, Swati Rawat and Pashupati Nath
DOI: 10.2174/9789815274349124010012
PDF Price: $15
Abstract
The Internet of Things (IoT) technology is making a radical transition in the
agricultural business, resulting in the creation of precision agriculture and sustainable
crop management practices. This study inspects how Internet of Things (IoT)
technology is revolutionizing agriculture, with a particular emphasis on sustainable
crop management techniques and precision agriculture. The study explores the extent
and significance of using sensors, IoT devices, and data analytics for improved crop
monitoring and management, empowering farmers to make data-driven choices.
Farmers are able to allocate resources more efficiently and produce less waste due to
the real-time data collecting on soil moisture, temperature, humidity, and crop health.
We go into great detail on the essential elements of IoT-based precision agriculture,
such as decision support systems, data collecting, analytics, and sensor technology. The
study also looks at the benefits of using IoT in agriculture, highlighting how
technology might completely transform farming methods for more sustainability and
efficiency. A thorough literature study adds to our understanding of the status of
research in Internet of Things applications for sustainable crop management and
precision agriculture.
Scientific Integrated Solid Waste Management System to Minimize Adverse Effects on Agriculture
Page: 201-218 (18)
Author: Megha Jain* and Dhiraj Pandey
DOI: 10.2174/9789815274349124010013
PDF Price: $15
Abstract
The management of solid waste is a major issue everywhere in the world. It
is an undesirable material produced from industrial and business activities andfrom
residential areas in a given region, which leads to adverse impacts on agriculture.
Decentralized municipal solid waste is one of the causes of the harmful environment in
India and all over the world. Decentralized waste management causes significant
problems, including hazardous diseases and environmental pollution. To tackle these
problems, scientific management of waste disposal is needed. Few methods are used to
find the solution to these problems, but they do not give precise and accurate results.
Moreover, there is uncertainty in data, so there is an immediate need to establish a
reliable way to find a place where solid waste can be disposed of. A scientific,
integrated solid waste management system must be immediately designed to reduce the
effects on agriculture. Geospatial tools like Remote Sensing and GIS, which can help in
appropriate site choice for Municipal Solid Waste (MSW) disposal in an additional
scientific manner, might result in economically supported concrete proof. The study
provides the suitable places in the city and the best algorithms in the field of Site
Suitability Analysis (SSA).
Subject Index
Page: 219-224 (6)
Author: Kavita Pandey, Shikha Jain, Dhiraj Pandey and Omprakash Kaiwartya
DOI: 10.2174/9789815274349124010014
Introduction
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