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Intelligent Systems and Sustainable Computational Models

Concepts, Architecture, and Practical Applications
 
Kiadás sorszáma: 1
Kiadó: Auerbach Publications
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Kiadói listaár:
GBP 160.00
Becsült forint ár:
77 280 Ft (73 600 Ft + 5% áfa)
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Az Ön ára:
61 824 (58 880 Ft + 5% áfa )
Kedvezmény(ek): 20% (kb. 15 456 Ft)
A kedvezmény érvényes eddig: 2024. június 30.
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Rövid leírás:

This book examines how intelligent systems can help solve such environmental problems such as rising human population, climate change, and the depletion of natural resources. It offers systems implementations that can benefit researchers and professionals.

Hosszú leírás:

The fields of intelligent systems and sustainability have been gaining momentum in the research community. They have drawn interest in such research fields as computer science, information technology, electrical engineering, and other associated engineering disciples. The promise of intelligent systems applied to sustainability is becoming a reality due to the recent advancements in the Internet of Things (IoT), Artificial Intelligence, Big Data, blockchain, deep learning, and machine learning. The emergence of intelligent systems has given rise to a wide range of techniques and algorithms using an ensemble approach to implement novel solutions for complex problems associated with sustainability.


Intelligent Systems and Sustainable Computational Models: Concepts, Architecture, and Practical Applications explores this ensemble approach towards building a sustainable future. It explores novel solutions for such pressing problems as smart healthcare ecosystems, energy efficient distributed computing, affordable renewable resources, mitigating financial risks, monitoring environmental degradation, and balancing climate conditions. The book helps researchers to apply intelligent systems to computational sustainability models to propose efficient methods, techniques, and tools. The book covers such areas as:



  • Intelligent and adaptive computing for sustainable energy, water, and transportation networks

  • Blockchain for decentralized systems for sustainable applications, systems, and infrastructure

  • IoT for sustainable critical infrastructure

  • Explainable AI (XAI) and decision-making models for computational sustainability

  • Sustainable development using edge computing, fog computing and cloud computing

  • Cognitive intelligent systems for e-learning

  • Artificial Intelligence and machine learning for large scale data

  • Green computing and cyber physical systems

Real-time applications in healthcare, agriculture, smart cities, and smart governance.


By examining how intelligent systems can build a sustainable society, the book presents systems solutions that can benefit researchers and professionals in such fields as information technology, health, energy, agricultural, manufacturing, and environmental protection.

Tartalomjegyzék:

1. Smart Power Management in Data Centers Using Machine-Learning Techniques, 2. Exploring the Power of Deep Learning and Big Data in Flood Forecasting: State-of-the-Art Techniques and Insights, 3. Storage Management Techniques for Medical Internet of Things (MIoT), 4. A Study on Trending Technologies for IoT Use Cases Aspires to Build Sustainable Smart Cities, 5. Hydro-Meteorological Disaster Prediction Using Deep Learning Techniques, 6. Assessment of ICT for Sustainable Developments with Reference to Fog and Cloud Computing, 7. Explainable Artificial Intelligence (XAI) for Computational Sustainability: Concepts, Opportunities, Challenges, and Future Directions, 8. Edge Computing-Based Intrusion Detection Systems: A Review of Applications, Challenges, and Opportunities, 9. Recent Advancements in IoT Security-Based Challenges: A Brief Review, 10. An Approach to Smart Targeted Advertising Using Deep Convolutional Neural Networks, 11. Text Classification of Customer and Salesperson Conversations to Predict Sales Using Ensemble Models, 12. Sentimental Analysis on Amazon Book Reviews: A Deep Learning Approach, 13. A Deep LSTM Recurrent Learning Approach for Sentiment Analysis on Movie Reviews, 14. Cognitive Intelligent Personal Learning Assistants for Enriching Personalized Learning, 15. Natural Language Processing for Fake News Detection Using Hybrid Deep Learning Techniques, 16. A Comparative Analysis of Deep Learning Models for Fake News Detection and Popularity Prediction of Articles, 17. Internet of Things (IoT)-Based Smart Maternity Healthcare Services, 18. A Real-Time Automated Face Recognition and Detection System for Competitive Examination, 19. Medical Image Analysis with Vision Transformers for Downstream Tasks and Clinical Report Generation, 0. Ensemble Embedding and Convolutional Neural Network-Based Big Data Framework for Structure Prediction of Proteins, 21. Deep Learning-Based Automated Diagnosis and Prescription of Plant Diseases, 22. Intelligent Farming Through Weather Forecasting Using Deep Learning Techniques for Enhancing Crop Productivity, 23. Plant Disease Detection and Classification Using a Deep Learning Approach for Image-Based Data, 24. Deep Learning-Based Object Detection in Real-Time Video, 25. Prediction of COVID Stages Using Data Analysis and Machine Learning, 26. A Statistical Analysis of Suitable Drugs for Major Drug Resistant Mutations in the HIV-1 Group M Virus