PMNGC 2023 : Predictive Methods in Next-Generation Computing

Predictive Methods in Next-Generation Computing
Call for Book Chapters


Computing technologies are significantly reconnoitering in all the sectors and trying to provide an automated energy efficient solution for various real-world problems with an advanced predictive model. This book explores the computing technologies in various domains, aims to provide novel strategies and design thoughts for smart, secured and sustained environment for future.
This book provides a realistic overview of various computer technologies which have made drastic advances in the field of smart applications resulting into smart agriculture, healthcare, traffic management and sustainability. The book talks about Predictive models in the arena of AI, ML and IoT. The book considers the scenarios with technology augmentations of AI/ML/IoT in various smart applications for smart and safe future of humans. Few chapters will also include case studies related to the above-said topics and will be detailed to make readers to get a glimpse, how beneficial it would be to integrate technology into predictive analytics to make it more automated energy efficient and safe additionally making it profitable for businesses also.

The topics are related to but not limited to the following:
1. Introduction to Intelligent Computational Technologies for Smart and Sustainable Applications.
2. Era of Intelligent Computational Techniques (AI/ML/IoT/Big Data Analytics) in Smart and Sustainable Applications.
3. Intelligent computational techniques in the design of smart and sustainable applications.
4. Framework for Smart Applications: A Step toward Sustainable Development.
5. Modern Architecture for Smart Applications in the field of Traffic Management.
6. Intelligent Transport Systems and Traffic Management Frameworks: A Sustainable approach.
7. Intelligent of Things in the smart and secure application development for sustainability.
8. Security and Privacy issues in data processing with predictive models.
9. Applications of intelligent computational techniques in the development of smart cities.
10. Predictive intelligence of things enabled waste management model in smart and sustainable environment.
11. Intelligent Predictive Analytics for Sustainable Global Development and Maintenance in Renewable Energy Sources.
12. Collaborative Technologies-initiated learning processes and digital twins suggested for enhanced learning of intelligent models.
13. Research challenges in the design and development of smart applications from sustainable perspective.
14. Analytical framework for smart and sustainable applications with energy optimization.
15. Futuristic Approach to Energy Efficient Methods for Smart and Sustainable Applications.


Chapter description
Chapter 1.
Introduction to Intelligent Computational Technologies for Smart and Sustainable Applications
Computational Intelligence refers to ability of computer to learn specific task from experimental observation or data. This chapter provides the introduction to concept of intelligent computing technologies and how it has brought innovation in smart applications.
Chapter 2.
Era of Intelligent Computational Techniques (AI/ML/IoT/Big Data Analytics) in Smart and Sustainable Applications.
This chapter provides the detailed study on the evolution of technologies and its predominant role in the development of smart applications involving sustainability. The chapter also explores the intelligent computational technologies in the recent developmental areas of healthcare, and traffic management.
Chapter 3.
Intelligent computational techniques in the design of smart and sustainable applications.
This chapter provides the wide-ranging investigation on the methods and frameworks used in the design of smart and sustainable application and how technology has reshaped the things in the present generation with smart intelligence.

Chapter 4.
Framework for Smart Applications: A Step toward Sustainable Development.
This chapter explores the tremendous growth in smart applications and its sustainable growth and development. The chapter also provides a framework/architecture intend to design an energy-efficient smart applications which can sustain for the smarter future.

Chapter 5.
Modern Architecture for Smart Applications in the field of Traffic Management.
This chapter fetches the architectural design involved in the analytics of smart applications in various domains namely healthcare, traffic management, waste management, etc. Intelligent predictive model supports sustainable development by ensuring green and safe environment, reducing bottlenecks and improving efficiency. This will be illustrated with a case study.
Chapter 6.
Intelligent Transport Systems and Traffic Management Frameworks: A Sustainable approach
Smart transportation plays a predominant role in the development of smart traffic management systems. Big Data, IoT and Intelligent systems collaboratively brings out an innovative framework for ITS. This chapter explores the theme of intelligent systems focused on energy-efficiency for sustainability and presents the workflow of the model involved in the framework.
Chapter 7.
Intelligent of Things in the smart and secure application development for sustainability.
This chapter explores how intelligence of things could unlock new sources for smart and secure applications development which can be safe and secure for communities. The role of AI/ML and Big data analytics in smart intelligence systems will be a primary factor focused in this chapter.
Chapter 8.
Security and Privacy issues in data processing with predictive models
Predictive models are to be wise in making decisions and at the same time, it should have proper secure mechanisms to protect the data securely. This chapter explores the security and privacy issues in processing and storing the data, and also will provide a solution to handle these issues in an effective manner.

Chapter 9.
Applications of intelligent computational techniques in the development of smart cities
This chapter explores the importance of smart applications in various aspects of smart cities and presents a mechanism involved in the development of any smart application with the technologies namely IoT, AI, Big Data and ML. The chapter also addresses the necessity of these applications and how they can move the life to next level with a case study illustration.
Chapter 10.
Predictive intelligence of things enabled waste management model in smart and sustainable environment
This chapter explores the concept of predictive analytics with a model demonstrating the importance of intelligence of things in managing a smart application in an automated and secure way. Intelligence of Things is quite important in the design and development of an energy-efficient solution.

Chapter 11.
Intelligent Predictive Analytics for Sustainable Global Development and Maintenance in Renewable Energy Sources
This chapter explores the predictive analytics intended to design a global application and maintaining with energy sources. Renewable energy sources are necessary to maintain a green and pollution less environment, resulting in the better safer of human lives.

Chapter 12.
Collaborative Technologies-initiated learning processes and digital twins suggested for enhanced learning of intelligent models.
This chapter explores the arrival of the fourth industrial revolution, which is better known as Industry 4.0, the manufacturing sector has seen a holistic shift from conventional automated systems to one that is driven by Internet of Things (IoT) and cloud computing involving cyber physical systems. A digital twin system is presented along with its design considerations for enhanced learning of intelligent models.

Chapter 13.
Research challenges in the design and development of smart applications from sustainable perspective.
This chapter explores the research challenges involved in providing an energy-efficient smart applications. A smart mechanism needs to be implemented in place to effectively manage the natural resources and assets within cities to ensure the sustainability of services and to provide a high quality of life to residents. This chapter elaborates on the current state-of-the-art in the techniques of computational engineering in the context of smart applications focused on smart cities, and smart traffic management.

Chapter 14.
Analytical framework for smart and sustainable applications with energy optimization.
Energy serves as a crucial component of urban life because it supports the entire spectrum of economic activities and ensures a certain level of quality of life for residents. Through these constraints, cities must change and develop in a smart way, without ignoring issues of energy efficiency and sustainability. In this regard, the chapter intends to present a decision - making support framework capable of assessing and optimizing energy use in Smart applications.

Chapter 15.
Futuristic Approach to Energy Efficient Methods for Smart and Sustainable Applications.
The chapter focuses on existing, novel, and expanding sensors, communication methods and protocols, artificial intelligence techniques and machine learning, green energies, and energy harvesting. They are all capable of allowing high-performance intelligent systems to fine tune energy consumption and user convenience. Furthermore, it discusses the most appropriate technologies and techniques, as well as their main characteristics and applications and explores the futuristic approaches in attaining better and smart applications for greater community.

Editors:
R. Sathiyaraj
Department of CSE
GITAM School of Technology
GITAM University, NH 207
NagadenehalliDoddaballapur, taluk, Bengaluru, Karnataka 561203, India

Rajesh Kumar Dhanaraj
Symbiosis International (Deemed University), India

K. Arun Kumar
Department of CSE
GITAM School of Technology
GITAM University, NH 207
NagadenehalliDoddaballapur, taluk, Bengaluru, Karnataka 561203, India

Rutvij H. Jhaveri
Department of Computer Science and Engineering, School of Technology,
Pandit Deendayal Energy University, India

A.Mohamed Abbas
Faculty-Information Technology Department,
University of Technology and Applied Sciences-Sur,
Sultanate of Oman, P.O. Box: 484,
Zip Code: 411, Sur.

Submission link: https://easychair.org/conferences/?conf=pmngc2023

For any queries, please email to [email protected]