This book presents the outcome of two-day 2nd International e-Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering and Technology (ICSISCET 2020) held at Madhav Institute of Technology & Science (MITS), Gwalior, India, from December 18–19, 2020. The book extensively covers recent research in artificial intelligence (AI) that knit together nature-inspired algorithms, evolutionary computing, fuzzy systems, computational intelligence, machine learning, deep learning, etc., which is very useful while dealing with real problems due to their model-free structure, learning ability, and flexible approach. These techniques mimic human thinking and decision-making abilities to produce systems that are intelligent, efficient, cost-effective, and fast. The book provides a friendly and informative treatment of the topics which makes this book an ideal reference for both beginners and experienced researchers.

The book is a collection of best selected research papers presented at the International Conference on Intelligent Systems and Sustainable Computing (ICISSC 2021), held in School of Engineering, Malla Reddy University, Hyderabad, India, during 24–25 September 2021. The book covers recent research in intelligent systems, intelligent business systems, soft computing, swarm intelligence, artificial intelligence and neural networks, data mining & data warehousing, cloud computing, distributed computing, big data analytics, Internet of Things (IoT), machine learning, speech processing, sustainable high-performance systems, VLSI and embedded systems, image and video processing, and signal processing and communication.

HANDBOOK OF INTELLIGENT COMPUTING AND OPTIMIZATION FOR SUSTAINABLE DEVELOPMENT This book provides a comprehensive overview of the latest breakthroughs and recent progress in sustainable intelligent computing technologies, applications, and optimization techniques across various industries. Optimization has received enormous attention along with the rapidly increasing use of communication technology and the development of user-friendly software and artificial intelligence. In almost all human activities, there is a desire to deliver the highest possible results with the least amount of effort. Moreover, optimization is a very well-known area with a vast number of applications, from route finding problems to medical treatment, construction, finance, accounting, engineering, and maintenance schedules in plants. As far as optimization of real-world problems is concerned, understanding the nature of the problem and grouping it in a proper class may help the designer employ proper techniques which can solve the problem efficiently. Many intelligent optimization techniques can find optimal solutions without the use of objective function and are less prone to local conditions. The 41 chapters comprising the Handbook of Intelligent Computing and Optimization for Sustainable Development by subject specialists, represent diverse disciplines such as mathematics and computer science, electrical and electronics engineering, neuroscience and cognitive sciences, medicine, and social sciences, and provide the reader with an integrated understanding of the importance that intelligent computing has in the sustainable development of current societies. It discusses the emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative intelligent techniques in a variety of sectors, including IoT, manufacturing, optimization, and healthcare. Audience It is a pivotal reference source for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in the field of artificial intelligence in the areas of Internet of Things, renewable energy, optimization, and smart cities.

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.

This book constitutes selected and revised papers of the First International Conference on Artificial Intelligence and Sustainable Computing for Smart City, AIS2C2 2021, held in Greater Noida, India, in March 2021. Due to the COVID-19 pandemic the conference was held online. The 17 full papers and 3 short papers included were thoroughly reviewed and selected from 204 submissions. They are organized in the following topical sections: ​sentimental and emotions analysis for smart cities; smart specialization strategies for smart cities; security in smart cities; advances applications for future smart cities; healthcare in smart cities; machine learning applications in smart cities.

This book delves into various solution paradigms such as artificial neural network, support vector machine, wavelet transforms, evolutionary computing, swarm intelligence. During the last decade, novel solution technologies based on human and species intelligence have gained immense popularity due to their flexible and unconventional approach. New analytical tools are also being developed to handle big data processing and smart decision making. The idea behind compiling this work is to familiarize researchers, academicians, industry persons and students with various applications of intelligent techniques for producing sustainable, cost-effective and robust solutions of frequently encountered complex, real-world problems in engineering and science disciplines. The practical problems in smart grids, communication, waste management, elimination of harmful elements from nature, etc., are identified, and smart and optimal solutions are proposed.

This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors. It also discusses new models, practical solutions and technological advances related to the development and the transformation of cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

This book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI applications and financial technologies to develop future strategies and to achieve sustainable development goals.

The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. - Introduces new deep learning models developed to address sustainable solutions for issues related to agriculture - Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable agriculture - Illustrates through case studies how deep learning has been used to address a variety of agricultural diseases that are currently on the cutting edge - Delivers an accessible explanation of artificial intelligence algorithms, making it easier for the reader to implement or use them in their own agricultural domain