eChapters

Data science supports precision agriculture by converting large and varied agricultural datasets into actionable knowledge. Information from soil sensors, weather stations, satellites, drones and smart machinery can guide field preparation, sowing, irrigation, fertilization, pest control and harvesting. This chapter examines data collection, storage, analytics, machine learning, predictive modelling and real-time IoT monitoring. It explains how these tools can optimize water, nutrients, energy and other agricultural inputs while improving productivity and sustainability. Implementation challenges include high costs, insufficient technical knowledge, privacy concerns and inadequate digital infrastructure. Emerging cloud, edge, blockchain and artificial-intelligence technologies are discussed as mechanisms for advancing climate-smart and data-driven agricultural management.

Introduction
 
Electronic resources for libraries includes online databases , electronic( e-) journals , electronic(e-) books ,full text articles and web sites, where online journals have firmly established themselves as essential resources for libraries and information centers  and their users, as appointed books in most of disciplines. Electronic books (e-books) have not found the same favour. The potential of e-books to support learning activity has been acknowledged, and new services have emerged in recent years, but uptake has been slow.

1. Introduction

An expert system is defined as “a computer program designed to model the problem solving ability of a human expert” (Durkin, 1994). It is also defined as “a system that uses human knowledge captured in a computer to solve problems that ordinarily require human expertise”. An intelligent computer program that uses knowledge and inference procedures to solve problems that was difficult enough to acquire significant human expertise for their solutions. It is a computer application that solves complicated problems that would require extensive human expertise. To do so, it simulates the human reasoning process by applying specific knowledge and interfaces. Expert system also uses human knowledge to solve problems that normally

Starting from the middle of the 20^th Century, information has become a commodity. Those best able to access information will be more successful than their peers in their future careers. Technological competence will be as important as medical competence to practice at the highest levels. Advances in computer technology have made access to veterinary and medical databases much simpler than in the past. It is quite likely that in the future, it will be a malpractice for practitioners not to access online information essential to the treatment of their patients. Wireless digital transfer of information will make access to necessary information independent of time and place.

Veterinary medicine and educational delivery are becoming an increasingly international market. Those who are prepared to deliver material in this manner will have a competitive advantage. Use of digital technologies will allow veterinary colleges to share information, including class material, more efficiently. This will enable each college to market specific educational information for students at other veterinary colleges or continuing education modules to graduate veterinarians around the world. On-line certificate programmes in specific veterinary topics will be developed. Use of computer technologies can enrich the teaching environment. By digitizing library, classroom, and laboratory visual images, students can access these materials at any time or place, freeing them from library and classroom schedules. Medical colleges have found that students heavily use these image resources. Computer technologies provide both horizontal and vertical integration of the professional curriculum, allowing students to explore information to the depth at which they are comfortable, without regard to their “year of study” in a traditional “linear” curriculum. Allowing students to see future applications of current learning material provides additional incentive to master basic material. Computers are a tool, just like a textbook, notebook, or calculator.

3.1 Introduction

Internet of Things (IoT) allows computational devices and sensory support to connect with each other and access services on the Internet. The IoT idea was introduced to connect devices through the Internet and facilitate access to information for users. The potential application of IoT includes agriculture. The aim of this chapter is to explain the role of NodeMCU in the agriculture field. NodeMCU is IoT module which can be used to present the IoT concept as a basis for monitoring and control. The systems used in farm production processes. NodeMCU play a key role, with a focus on their realization by available microcontroller platforms and appropriate sensors. IoT based system provides opportunity to users to monitor and control the process remotely.

1. Introduction

Universal development through Education for all had been a prominent feature earlier during Millennium Development Goals and recently it has gained a fresh momentum when United Nations General Assembly set 17 inspirational Sustainable development Goals. Quality Education is the focus of SDG 4, “Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” (Sustainable Development Goals, 2023). Role of education in achieving these sustainable development goals in developing countries is well recognized by OECD. OECD in its report on ‘Education at a Glance 2013’ states that “Educational attainment is frequently used as a measure of human capital and the level of an Individual’s skills. The level of educational attainment is the percentage of population that has reached a certain level of education. Higher levels of educational attainment are strongly associated with higher employment rates” (OECD, 2013). Furthermore, OECD in its report published in 2017 explains that “Making SDG 4 a reality will transform lives around the globe. Education is so central to the achievement of a sustainable, prosperous, and equitable planet that failure to achieve this particular SDG puts at risk the achievement of the 17 SDGs as a Whole” (OECD, 2017).

Establishment of databases and data warehouse; knowledge discovery from database/data warehouse (KDD) and development of the mechanism of dissemination of knowledge on information networks as per requirements of user groups is gaining importance now a days. Since there is a large number of data collection agencies and equally diverse resources for which the information is collected, it is easy to visualize the heterogeneity of information. The problem is compounded by the fact that there are no common standards that are applied in data collection. Designing data warehouses to integrate the collected information poses a formidable challenge to any data warehouses architect. In order to use the information for planning and decision-making level, data have to be integrated and aggregated properly.

Introduction

The libraries of 2020 become multi-media centres of information resources, leaving behind their dull and drab image of repositories of old dusty books materials like micro-films, audio and video cassettes. Various electronic products for use both off line and on line representing the special type of materials need special equipments of different makes for their effective use.

Introduction

The library and information centre is an important component of any educational institution. It is a hub of specific information where the end users can explore the vast resources of information. In the era of old age libraries users had to spend more time for searching a small piece of information and for that had to depend on library professionals. But now we are living in the age of information and communication technology, computers are being used for day-to-day work of library which saves the time of users and avoid the redundancy work of library staff.

Abstract
    
The amount of data being collected across a wide variety of fields today far exceeds our ability to reduce and analyze without the use of automated analysis techniques. In addition, the whole data may not be of user interest and imperfect. Therefore, it is very challenging to organize this data in formal system, which provides outputs in more relevant, useful, and structured manner. There are many techniques available to retrieve knowledge from this voluminous data. This paper discusses different rough computing based information retrieval techniques to obtain meaningful knowledge from large amount of datasets. We also discuss a real life example to show the viability of proposed research.

Introduction 
The transformative potential of digital technologies in reshaping governance and development paradigms is increasingly evident, particularly in rural contexts. In India, where nearly 65% of the population resides in rural areas, the imperative to leverage digital tools for inclusive growth has never been more critical. Rural digital governance refers to the strategic use of information and communication technologies (ICTs) to enhance service delivery, improve livelihoods, and foster participatory development in rural areas. It encompasses various applications from digital health, education, and financial inclusion to precision agriculture, market linkages, and entrepreneurial enablement, each designed to address long-standing structural inequities. Historically, rural regions have been perceived as passive recipients of policy support and welfare interventions. However, with the advent of digital technologies, these areas are increasingly positioned to become both demand drivers through rising incomes and service consumption and supply hubs, contributing to national productivity through digitally enabled livelihoods and enterprises. By enhancing access to essential services, improving the efficiency of traditional sectors such as agriculture and handicrafts, and facilitating diversification into non-farm activities like rural tourism and agri-processing, digital governance catalyzes rural transformation. However, the success of rural digital governance is contingent upon adopting a holistic and contextualized approach. One-size-fits-all digital interventions often fail to address the nuanced realities of rural economies. Effective rural technology deployment requires carefully diagnosing local needs, infrastructural capabilities, and livelihood profiles. In this regard, a participatory approach to technology selection and design grounded in the realities of rural life ensures greater relevance, uptake, and impact. Publicprivate partnerships (PPPs) play a pivotal role in scaling such initiatives, with governments providing scale and legitimacy while private actors contribute innovation, technical know-how, and financial investment.

7.1 Meaning of Sampling
    
Before we consider sampling theory, we first define the terms population and sample.
 
The word ‘population’ or ‘universe’ in statistics is used to refer to any collection of individuals or of their attributes or of results of operations which can be numerically specified. For example the assemblage of heights of all the individuals in the population is called a population of heights.  Similarly we may consider the population of weights, wages, yields of grain; prices of wheat, mileages of automobile tyres, etc. a population containing a finite number of individuals or members is called a finite population.  For instance the population f ages of the workers in a factory constitute a finite population of ages. A population with infinite number of members is known as infinite population.  For example the population of pressures of temperatures at various points in the atmosphere is an infinite population. 

ABSTRACT

Village Resource Centre (VRC) provides information services to the rural population to empower them to face day to day challenges. In this line, the Department of Space, ISRO & RRSSC is bringing its space technology to common man by setting up of Village Resource Centres, with a view to integrate the capabilities of communication and remote sensing satellites to address the changing and critical needs of rural communities. VRC is totally interactive VSAT based network for providing space enabled information related to land records, natural resources, drinking water wells, ground water recharge, soil types, alternate cropping pattern, waste lands, etc. VRCs also provide  variety of services in its tele-education and tele-medicine programmes, online decision support, weather forecasting, water management, interactive farmers advisory services (video conferencing) etc.

10.1 Introduction

The objective of this chapter is to develop a data logger and indicator for fire detection in agriculture field. The data logger is designed with the help of Scilab. The system comprises of Ardiuini Nano, light sensor, MQ6, MQ135, IR sensor, temperature sensor, power supply. The system is designed to take sensory data on Scilab with serial communication. Fig.10.1 shows block diagram for a system. Table.10.1 shows the component list required to develop the system.

1. Introduction

Today, all the organisations rely on assessments of data provided by their users, consumers, internal procedures, and day to day operations to find new avenues for betterment and expansion of the product and services. These insights provide a large and intricate set of professionally generated, maintained, analyzed, and modified facts. "Big Data" refers to the vast amount of data (Bansal, 2022, April 6). For instance, social media platforms facilitate human contact every day and millions of people connect and share a vast array of diverse types of information through these platforms. Big Data is viewed as "incredibly significant" in academic research. In the Big Data context, data visualization tools and technologies are essential for analyzing large amounts of data and making decisions based on facts (Adilin Beatrice, 2021, March 2). Information and data are represented graphically in data visualization. By using visual components like charts, graphs, and maps, data visualization tools provide an intuitive way to observe and understand trends, outliers, and patterns in data. The process is called Big Data Analytics that describes the process of uncovering trends, patterns, and correlations in large amounts of raw data to help make data-informed decisions in various research works.

One of the major goals in agricultural crop management is to achieve maximum yield with minimum investment while maintaining a good quality of the crop produce. Crop infestation due to insects, diseases, and weeds are some of the major factors responsible for loss in crop yield. Further, an efficient Precision Agriculture Crop Management System is one, which is capable of precisely detecting the crop yield indicators (or crop health parameters) at an early stage and can predict the yield at any point of time of the crop cycle.

Sensor is a physical device used to detect manifestations or variations in a process value and collect data in real time assessment mode for measuring and predicting system/device performance and finally analyzing it to attain a specific task or application. Sensor technology is now-a-days used for interdisciplinary applications for data collection, system analysis and monitoring.

Abstract

Sequence alignment is the positioning of DNA, RNA, or protein sequences with each other to identify the regions of identity, which may be the result of functional, structural, or evolutionary relationships between the sequences. Therefore, sequence alignment is the process of aligning two sequences to achieve the maximum levels of identity and conservation. This chapter deals with the basic concept of sequence alignment and the tools associated with multiple sequence alignment. Further, it describes various matrices used in sequence alignment.

Learning objectives

1. Recognise inflammatory cell types

2. Recognise common skin pathogens

3. Diagnostic test are best for each case

4. Gain experience in interpretation

5. Recognise important artefacts

″The most crucial step towards healing is having the right diagnosis″. While approaching a case, a clinician should follow appropriate steps in a systematic way for accurate diagnosis of dermatological disorders. A careful history is a first step to choose appropriate diagnostic tests.

By 2050, the global population is projected to reach approximately 9.8 billion, requiring a 70% increase in food production to meet the growing dietary demands. The livestock sector will play a crucial role in addressing this rising need through sustainable animal production, contributing to food security, poverty alleviation, public health, and food safety. To tackle the challenges posed by population growth and to achieve the United Nations Sustainable Development Goals (SDGs), technological advancements and innovations will be essential in transforming the food and agriculture sectors.

In light of these challenges, Veterinary Services are more critical than ever. They are essential for enhancing livestock health and productivity, ensuring high-quality food that meets safety standards, and mitigating risks associated with animal diseases and public health. Additionally, Veterinary Services must contribute to global efforts in addressing issues such as food security, antimicrobial resistance, climate change, and the depletion of natural resources.