Book Volume 1
Preface
Page: i-iii (3)
Author: Adarsh Garg, Valentina Emilia Balas, Rudra Pratap Ojha and Pramod Kumar Srivastava
DOI: 10.2174/9789815165791123010001
Agent Interactions Environments
Page: 1-13 (13)
Author: Kuldeep Singh Kaswan*, Jagjit Singh Dhatterwa and Ankita Tiwari
DOI: 10.2174/9789815165791123010004
PDF Price: $15
Abstract
Digitization has a substantial impact on almost all facets of fashion, starting
from the designing of a fashion item to its production and its usage by consumers.
Fashion has always been evolving with emerging technologies. With the beginning of
Artificial Intelligent (AI) enabled technologies, the fashion industry has become as
dynamic as technology, emerging as a forward-looking trend giant. The impact of AI
on the augmentation of fashion trends is unquestionable and the industry has witnessed
its fast move from 4.0 to 5.0 with the use of advanced technology. Although fashion is
changing at a very fast pace with AI, fashion professionals have raised the socioeconomic impact of AI on the fashion industry, including the Green Economy (GE)
issues, thus, making the exploration of the phenomenon essential. This chapter explores
how AI-enabled technology in the fashion industry and fashion environment, is
influencing the GE status of the fashion industry, especially in the post-COVID-19 era
of innovative e-commerce fashion.
Strengthening Corporate Social Responsibility Practices through Artificial Intelligence
Page: 14-25 (12)
Author: A. Menaga, Yasmeen Bano, S. Vasantha* and Narendranath Uppala
DOI: 10.2174/9789815165791123010005
PDF Price: $15
Abstract
Artificial intelligence (AI) has gained enormous usage in business in recent
years. Still, in regard to measuring business ethics and morality, otherwise called
corporate social responsibility, the use of Artificial Intelligence is limited to a greater
extent. In this regard, the purpose of the study is to conceptually formulate the
implementation of AI in CSR programs. For gathering data, the study utilised a
structured questionnaire. Employers from a range of governmental and commercial
organisations provided the primary data for the study. Using AMOS 21's Structural
Equation Modelling (SEM) and SPSS 21, the projected model was empirically tested.
The Research concludes that AI can strengthen effective CSR practices. The research
also uses SEM to establish a cause-and-effect connection between the research
variables.
Role of Artificial Intelligence in Healthcare Management
Page: 26-47 (22)
Author: Amit Bhaskar, Pankaj Yadav, Savendra Pratap Singh*, Vijay Kumar, Sambhrant Srivastava, Saurabh Kumar Singh, Brihaspati Singh and Akriti Dutt
DOI: 10.2174/9789815165791123010006
PDF Price: $15
Abstract
Artificial intelligence (AI) has recently become one of the most heavily
debated themes in the technological world. AI is active in numerous fields and now it
has lately entered the healthcare sector. In addition to biomarkers, the use of AI is
increasing in a variety of applications such as genetic editing, disease prediction and
diagnostics, drug development, personalized treatment, and so on. Accuracy in disease
diagnostics is essential for effective and efficient treatment as well as patient safety.
Artificial intelligence is a wide and varied field of data, analytics and continuously
evolving insights that meet the needs of the healthcare sector as well as patients. The
purpose of the many subsections in this book chapter is to shed light on how AI
integrated with machine learning (ML) & Deep-learning (DL) techniques operate in
various disease diagnosis domains, medication discovery, medical visualization, digital
health records, and electro-medical equipment.
Perspectives on Augmented and Virtual Reality (AVR) in Education: Current Technologies and the Potential for Education
Page: 48-69 (22)
Author: S. Christina Sheela*, V. Selvalakshmi and S.P.S. Arul Doss
DOI: 10.2174/9789815165791123010007
PDF Price: $15
Abstract
By combining information in the form of image alternatives with a software
programme that stores knowledge on real images, augmented and virtual reality (AVR)
technologies aid in the explanation of concepts. This methodology is developed to
improve educational learning through two-dimensional media in education. In bloom
taxonomy approach to teaching, integrating AR technology with academic content
results in a new kind of automated application that serves to reinforce the usefulness of
teaching-learning for learners in real-world situations. The learning outcome, which
includes knowledge level and performance engagement, has a significant impact on all
phases of higher education, from course planning to student evaluation and grading.
AVR is a novel technique that combines elements of omnipresent computing, tangible
computing, and social computing. This mode offers different affordances, combining
the physical and virtual worlds, with continuous and implicit purposes of reading and
interactivity. Digital resources are high-potential educational technology that enhances
learning by supporting the learning environment through numerous e-resources. The
various universities and Technical and Vocational Education Training (TVET)
institutions give students an opportunity to complete an experiential learning
component in their studies in order to complete their qualifications with the help of
AVR implementation. This chapter provides an introduction to Augmented and Virtual
reality (AVR) technology, the current status in education from different viewpoints,
key technologies, and strategies mentioned in the context of higher educational
learning output of students through these applications.
A New Approach to Crime Scene Management: AR-VR Applications in Forensic Science
Page: 70-88 (19)
Author: Vinny Sharma*, Rajeev Kumar, Kajol Bhati, Aditya Saini and Shyam Narayan Narayan Singh
DOI: 10.2174/9789815165791123010008
PDF Price: $15
Abstract
The crime scene, a place where a crime has been or is suspected to have
occurred or where the evidence related to a crime was found, is a vital part of the
investigation as it contains all the major information about a crime. A keen eye for the
crime scene can determine the possible Modus Operandi of a crime and establish
Corpus Delicti in a court of law. As per Indian law, we are allowed to visit a crime
scene once only and if we want to visit again, we have to take permission but it is of no
use. During a revisit to a crime scene, the chance or probability of finding any evidence is
nearly 0%. Documenting a crime thus became a very crucial step. By using ordinary
methods for documenting the crime scene we cannot give a visual or walk to the actual
crime scene. It’s just a physical view of the documents. It is, therefore, critical to
visually capture the crime scene and any potential evidence to aid the investigation.
The current demand is for Augmented Reality and Virtual Reality. Virtual Reality is a
wholly virtual view of the scenario, whereas Augmented Reality reflects a real-world
context. VR is a type of advanced user interface that comprises a real-time simulation
of a real-world environment with which the user interacts through numerous sensory
channels: sight, hearing, touch, smell, and taste. The 3D reconstruction and
visualization of crime situations such as criminal assaults, traffic accidents, and
homicides is a new method of criminal investigation that has the potential to improve
efficacy. To produce an accurate and immersive virtual environment, modern 3D
recording and processing methods, such as AR and VR, are used. Immersion in a
virtual environment, on the other hand, allows for various points of view.
The Influence of Green Supply Chain Management Practices Using Artificial Intelligence (AI) on Green Sustainability
Page: 89-100 (12)
Author: S. Susithra, S. Vasantha* and Kabaly P. Subramanian
DOI: 10.2174/9789815165791123010009
PDF Price: $15
Abstract
Rapid advances in artificial intelligence (AI) are enhancing the performance
of many sectors and enterprises, including green supply chain management. Innovative
technologies include machine learning, IoT, and big data. AI in the manufacturing
industry aims to utilise automation in production processes, better planning and
forecasting, and quality products. Small and medium enterprises play a significant role
in reducing carbon emissions, which has turned out to be an even more vital factor for
the manufacturing industry in the past two decades. Supply chain management is one
of the manufacturing’s utmost areas demanding a change. Sustainable procurement
enables firms to access resource recycling, efficient production, channel distribution,
and end consumption to lessen their environmental impact. The 2030 Agenda for
Sustainable Development (2015) is a well-thought-out synthesis of discussion that
establishes sustainable growth as a critical issue for the global community. The
accomplishment of sustainable goals makes it essential to develop a system of practice.
This is especially important for India, which has a history of high labour intensity and
industrialization. This review paper will analyse the future outlook of the market for
Artificial Intelligence (AI) in GSCM and green sustainability.
Multi-Agent Based Decision Support Systems
Page: 101-116 (16)
Author: Kuldeep Singh Kaswan*, Jagjit Singh Dhatterwal and Ankita Tiwari
DOI: 10.2174/9789815165791123010010
PDF Price: $15
Abstract
Multi-Agent-Based Decision Support Systems (MADSS) have emerged as
powerful tools for facilitating decision-making in complex and dynamic environments.
This chapter provides an overview of MADSS, highlighting their fundamental
concepts, key components, and applications. MADSS leverage the principles of multi-agent systems, artificial intelligence, and decision support systems to enable
collaborative decision-making among multiple autonomous agents. The chapter begins
by introducing the concept of multi-agent systems, emphasizing the advantages they
offer in terms of adaptability, flexibility, and scalability. It then explores the integration
of decision support systems within this framework, enabling agents to make informed
decisions by analyzing vast amounts of data, evaluating various alternatives, and
considering multiple criteria. The architecture of MADSS is discussed, focusing on the
interactions among agents, the coordination mechanisms employed, and the
information exchange protocols utilized. Various agent types, such as user agents,
decision agents, and knowledge agents, are described, along with their roles and
responsibilities within the system. The chapter further explores the different approaches
and techniques used in MADSS, including rule-based systems, expert systems,
machine learning, and optimization algorithms. It highlights the importance of agent
learning and adaptation to improve decision-making capabilities over time. The
applications of MADSS across various domains are presented, including finance,
supply chain management, healthcare, and transportation. Case studies illustrate how
MADSS can enhance decision-making processes, improve efficiency, and optimize
resource allocation in complex real-world scenarios.
Lastly, the chapter discusses the challenges and future directions of MADSS. Issues
such as agent coordination, trust among agents, and handling uncertainty are addressed.
The potential of integrating emerging technologies like blockchain, the Internet of
Things (IoT), and big data analytics is also explored, envisioning more sophisticated
MADSS capable of handling larger-scale problems.
An Artificial Intelligence Integrated Irrigation System: A Smart Approach
Page: 117-129 (13)
Author: Vibhooti Narayan Mishra*, Divya Pratap Singh and Radheshyam Dwivedi
DOI: 10.2174/9789815165791123010011
PDF Price: $15
Abstract
The farming sector is considered the backbone of the Indian economy. The
demand for water is continuously increasing with rising population density. Water is
frequently wasted on the land due to unscientific irrigation techniques and
unpredictable weather conditions. The efficiency of irrigation networks is challenged
by the extremely variable and farmer-dependent irrigation water demand. Each farm's
irrigation intensity is influenced by both accurate and inaccurate variables, as well as
the farmer's behaviour. Accurate and inaccurate variables include soil moisture, crop’s
water requirement, and climate conditions. An auto solar-powered smart irrigation
system enables users to accurately time watering cycles by tracking the soil moisture at
numerous sites across the field. This system also brings down the utilization of grid
power to save electricity as per the energy crisis for Indian farmers. The objective of
our work is to use an automated watering system to reduce the farmer's manual
involvement in the field at an effective cost. The artificial intelligence (AI) system is
based on sensing a control mechanism with required correction for the maximum
yielding of irrigation. It also optimizes the water requirement of a variety of crops. A
more accessible and more affordable solution to this issue is provided by the present
work. The conventional methods of irrigation used in India are sprinklers and floodtype systems. A large amount of water gets wasted, and crops are destroyed due to the
uneven slopes of the field. These problems can be resolved by incorporating an
intelligent automated irrigation system with an AI.
Leveraging AI for Smart Cities in India
Page: 130-141 (12)
Author: Manisha Singh*
DOI: 10.2174/9789815165791123010012
PDF Price: $15
Abstract
With the fast spread of connectivity via 5G and IoT (Internet of Things), the
Smart City Artificial Intelligence (AI) software industry is expected to reach a massive
value of $ 4.9 billion by 2025 globally [1]. In India, the AI market is slated to reach $
7.8 billion by 2025 at a CAGR of 20.2% as per an International Data Corporation
(IDC) report [2]. This chapter explains how AI can be used in the ambitious Smart
Cities Mission (SCM) announced by the Government of India in 2015 [3]. Beginning
with the conceptual understanding of the SCM, the chapter introduces AI as a useful
aid to urban planning thereby creating a safer and sustainable future for its citizens.
Applications of AI in Smart cities are then discussed followed by a brief discussion on
the prevailing best practices. Challenges in creating AI-enabled smart cities in India are
outlined followed by the conclusion which chalks out the road ahead for AI-enabled
smart cities in India
Virtual Reality to Augmented Reality: Need of the Hour in Human Resource Management
Page: 142-151 (10)
Author: Neerja Aswale, Pooja Agarwal and Archana Singh*
DOI: 10.2174/9789815165791123010013
PDF Price: $15
Abstract
AI-enabled Innovations and Green Economy in Fashion Industry
Page: 152-163 (12)
Author: Adarsh Garg* and Amrita Jain
DOI: 10.2174/9789815165791123010014
PDF Price: $15
Abstract
Digitization has a substantial impact on almost all facets of fashion, starting
from the designing of a fashion item to its production and its usage by consumers.
Fashion has always been evolving with emerging technologies. With the beginning of
Artificial Intelligent (AI) enabled technologies, the fashion industry has become as
dynamic as technology, emerging as a forward-looking trend giant. The impact of AI
on the augmentation of fashion trends is unquestionable and the industry has witnessed
its fast move from 4.0 to 5.0 with the use of advanced technology. Although fashion is
changing at a very fast pace with AI, fashion professionals have raised the socioeconomic impact of AI on the fashion industry, including the Green Economy (GE)
issues, thus, making the exploration of the phenomenon essential. This chapter explores
how AI-enabled technology in the fashion industry and fashion environment, is
influencing the GE status of the fashion industry, especially in the post-COVID-19 era
of innovative e-commerce fashion.
Subject Index
Page: 164-168 (5)
Author: Adarsh Garg, Valentina Emilia Balas, Rudra Pratap Ojha and Pramod Kumar Kumar Srivastava
DOI: 10.2174/9789815165791123010015
Introduction
Reinventing Technological Innovations with Artificial Intelligence delves into the transformative impact of Augmented and Virtual Reality (AVR) technology across industries. The book explores the merging of real and digital worlds, paving the way for personalized experiences in areas such as tourism, marketing, education, and more. With the potential to redefine business practices and societal norms in the era of Industry 4.0, AVR technologies hold untapped potential beyond gaming and entertainment. This volume presents a comprehensive overview of the current landscape, challenges, and prospects of integrating AVR with Artificial Intelligence (AI) for innovation and sustainability in various domains. The book presents 11 edited chapters contributed by technology and innovation experts that explore applications of AI, AR and VR technologies in different sectors in both public and private sectors. The editors have included reviews of technologies that impact human resource management, corporate social responsibility, healthcare, supply chain and criminal investigation. The reviews also highlight the role of AI in sustainable agriculture and smart cities. Key Features: Unveils the role of AVR in transforming real surroundings into digitally enhanced personal experiences. Explores AVR's applications beyond gaming in diverse sectors like marketing, construction, education, and more. Discusses challenges such as technical limitations, high costs, and resistance to adopting AVR. Addresses the need to enhance the reliability and effectiveness of AVR technologies in various industries. Provides a comprehensive perspective on AI innovations, AR, and VR technologies with real-world examples. The book is an informative reference for researchers, professionals, and experts in technology, innovation, who are interested in the convergence of Augmented and Virtual Reality with AI for practical applications in diverse industries.