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Intelligent Systems and Methods to Combat Covid-19 / edited by Amit Joshi, Nilanjan Dey, K. C. Santosh.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- SpringerBriefs in applied sciences and technology. Computational intelligence 2625-3704
- SpringerBriefs in Computational Intelligence, 2625-3704
- Language:
- English
- Subjects (All):
- Computational intelligence.
- Artificial intelligence.
- Medical informatics.
- Automatic control.
- Robotics.
- Mechatronics.
- Big data.
- Computational Intelligence.
- Artificial Intelligence.
- Health Informatics.
- Control, Robotics, Mechatronics.
- Big Data.
- Local Subjects:
- Computational Intelligence.
- Artificial Intelligence.
- Health Informatics.
- Control, Robotics, Mechatronics.
- Big Data.
- Physical Description:
- 1 online resource (XII, 91 pages) : 21 illustrations, 18 illustrations in color.
- Edition:
- First edition 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Singapore : Springer Singapore : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.
- Contents:
- Chapter 1. Data Analytics: COVID-19 Prediction using Multimodal Data
- Chapter 2. COVID-19 Apps: Privacy and security concerns
- Chapter 3. Coronavirus Outbreak: Multi-objective Prediction and Optimization
- Chapter 4. AI-Enabled Framework to Prevent COVID-19 from Further Spreading
- Chapter 5. Artificial Intelligence Enabled Robotic Drones for COVID-19 Outbreak
- Chapter 6. Understanding and Analysis of Enhanced COVID-19 Chest X-Ray Images
- Chapter 7. Deep Learning-based COVID-19 Diagnosis and Trend Predictions
- Chapter 8. COVID-19: Loose Ends
- Chapter 9. Social Distancing and Artificial Intelligence- Understanding the Duality in the times of Covid-19
- Chapter 10. Post Covid-19 and Business Analytics.
- Other Format:
- Printed edition:
- ISBN:
- 978-981-15-6572-4
- 9789811565724
- Access Restriction:
- Restricted for use by site license.
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