Artificial Intelligence Techniques for Sustainable Development (eBook, PDF)
Redaktion: Ghai, Deepika; Lata Tripathi, Suman; Dhir, Kanav; Rawal, Kirti
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Artificial Intelligence Techniques for Sustainable Development (eBook, PDF)
Redaktion: Ghai, Deepika; Lata Tripathi, Suman; Dhir, Kanav; Rawal, Kirti
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The book aims to increase the efficiency of the algorithms with a lesser number of computations as well as optimize the resources with cost-effective solutions.
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The book aims to increase the efficiency of the algorithms with a lesser number of computations as well as optimize the resources with cost-effective solutions.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 462
- Erscheinungstermin: 19. Dezember 2024
- Englisch
- ISBN-13: 9781040226148
- Artikelnr.: 72248007
- Verlag: Taylor & Francis
- Seitenzahl: 462
- Erscheinungstermin: 19. Dezember 2024
- Englisch
- ISBN-13: 9781040226148
- Artikelnr.: 72248007
Dr. Deepika Ghai has completed her Ph.D in the area of Signal and Image Processing from Punjab Engineering College (Deemed to be University), Chandigarh. She did her M.Tech in VLSI Design & CAD from Thapar University, Patiala, and B.Tech in Electronics and Communications Engineering from Rayat Institute of Engineering and Technology, Ropar. She is associated with Lovely Professional University as an Assistant Professor with more than six years of experience in academics. She has received Dr. C.B. Gupta Award in 2021 at Lovely Professional University. She has published more than 40 research papers in refereed journals and conferences. She has worked as a session chair, conference steering committee member, editorial board member, and reviewer in international/national IEEE Journal and conferences. She has also published a number of edited books, "Health Informatics and Technological Solutions for Coronavirus (COVID-19)" in CRC Taylor & Francis, "Machine Learning Algorithms for Signal and Image Processing" with Wiley-IEEE Press and "Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision" with Wiley Scrivener Publishing. She is associated as a life member of the Indian Science Congress. Her area of expertise includes Signal and Image Processing, Bio-medical Signal and Image Processing, and VLSI Signal Processing. Dr. Kirti Rawal received her Ph.D. degree in Electronics & Communication Engineering from Dr. B. R. Ambedkar National Institute of Technology Jalandhar in the area of Biomedical Signal Processing. Presently, she is working as a Professor in School of Electronics and Electrical Engineering at Lovely Professional University, Phagwara, Punjab India. She has published 16 research papers in reputed International Journals and 12 papers in Conferences. She is also guiding Ph.D. scholars, M. Tech Dissertation Students, and B. Tech. Projects in the area of biomedical signals, medical imaging, and digital signal & image processing. She has 13+ years of rich experience in teaching & research and technical education management. Her areas of interest are Digital Signal Processing, biomedical signal processing, medical imaging, artificial Intelligence, Image Processing, Machine Learning, and healthcare services. She is a member of the Indian Science Congress, Calcutta. She is the reviewer of many SCI-indexed Journals, Scopus-indexed Journals, and conferences. She has also authored and reviewed diverse chapters in refereed books. Dr. Kanav Dhir has completed his Ph.D in the area of Inorganic and Medicinal Chemistry from Punjab Engineering College (Deemed to be University), Chandigarh. He did his M.Sc in Chemistry from DAV College, Chandigarh, and B.Sc from A.S. College, Khanna. He is associated with DAV College, Chandigarh as an Assistant Professor with more than five 10 years of experience in academics. He has published more than 12 research papers in refereed journals and conferences and four book chapters. He has published an edited book, "Health Informatics and Technological Solutions for Coronavirus (COVID-19)" in CRC Taylor & Francis. His area of expertise includes Inorganic Chemistry and Bioinorganic Chemistry. He is associated as a professional member of SESI. Dr Suman Lata Tripathi is working as Professor in Lovely Professional University with more than 22 years of experience in academics and research. She has completed her Ph.D. in the area of microelectronics and VLSI Design from MNNIT, Allahabad. She did her MTech in Electronics Engineering from UP Technical University, Lucknow and BTech in Electrical Engineering from Purvanchal University, Jaunpur. She has completed her remote post-doc from Nottingham Trent University, London, UK in the year 2022-23. She has published more than 125 research papers in refereed Springer, Elsevier, IEEE, Wiley and IOP science journals, conference proceeding and e-books. She has also published 14 Indian patents and 4 copyright. She has guided 6 PhD scholar and 3 are under submission stage. She has organized several workshops, summer internships, and expert lectures for students. She has worked as a session chair, conference steering committee member, editorial board member, and peer reviewer in international/national IEEE, Springer, Wiley etc Journal and conferences. She has received the "Research Excellence Award" in 2019 and "Research Appreciation Award" in 2020, 2021 and 2023 at Lovely Professional University, India. She is recipient of IGEN Women's for Green Technology "Women's Achievers Award" on International Women's Day, 8th March-2023. She had received the best paper at IEEE ICICS-2018. She has also received funded project from SERB DST under the scheme TARE in the area of Microelectronics devices. She has edited and authored more than 27 books in different areas of Electronics and electrical engineering. She is associated for editing work with top publishers like Elsevier, CRC Taylor and Francis, Wiley-IEEE, SP Wiley, Nova Science and Apple academic press etc. She is also working as book series editor for title, "Smart Engineering Systems" CRC Press, "Engineering system design for sustainable developments" & "Decentralized Systems & Next Generation Internet" Wiley-Scrivener, and conference series editor for "Conference Proceedings Series on Intelligent systems for Engineering designs" CRC Press Taylor & Francis. She is serving as academic editor of journal "Journal of Electrical and Computer Engineering" (Scopus/WoS, Q2), "International Journal of Reconfigurable Computing, Scopus, Q3), "Active and Passive Electronic Component" (Scopus, Q4) Hindawi and special issue guest editor for "Advances in Nanomaterials and Nanoscale Semiconductor Applications" Material, MDPI Journal (SCI IF=3.74, Q2). She is associated as senior member IEEE, Fellow IETE and Life member ISC and is continuously involved in different professional activities along with academic work. Her area of expertise includes microelectronics device modeling and characterization, low power VLSI circuit design, VLSI design of testing, and advanced FET design for IoT, Embedded System Design, reconfigurable architecture with FPGAs and biomedical applications etc.
Part 1: Introduction to Artificial Intelligence in Green Technology. 1.
Introduction to Green and Red Artificial Intelligence. 2. Impact of
Artificial Intelligence Techniques on Green Applications. 3. Tools for
Artificial Intelligence in Green Applications. 4. Artificial Intelligence
for Human-Computer Interfaces. Part 2: Green Electronic Technology. 5.
Green Communication Technologies and Protocols. 6. Green Communication
Network Design and Implementation for Internet of Things Ecosystem. 7.
Smart Portable and Intelligent Internet of Things Enabled System for Green
Applications. 8. Green Computing in Network Security. 9. Artificial
Intelligence Models for Remote Sensing Applications. Part 3: Green Energy
Technology. 10. Energy Efficiency Models of Artificial Systems. 11.
Artificial Intelligence for Energy Storage Systems. 12. Smart Energy
Harvesting/Charging and Power Management Techniques using Machine Learning.
13. Renewable Energy Monitoring and Forecast based on Intelligent Data
Analysis. 14. Case Study on Artificial Intelligence Integration with Green
Energy Generation. Part 4: Green Environmental Solutions. 15. Green
Artificial Intelligence: Biodegradable and Biocompatible Materials. 16.
Artificial Intelligence in Nanotechnology for Green Applications. 17.
Virtually Going Green: The Role of Artificial Intelligence in Reducing
Pollution and Toxicity. 18. Prediction Models for Carbon Emission and
Sequestration. 19. Prediction Models for Environment Health. 20.
Predictions Models for Climate Change or Natural Disaster. 21. Air
Pollution Control. 22. Water Security and Ocean Technology. 23. Case Study:
Maintenance of Water Quality in Different Geographic Locations. Part 5:
Green Healthcare. 24. Digital Health Solutions with Bionic Devices. 25.
Smart Biomaterials. 26. Remote Health Monitoring and Telehealth. 27.
Optimization of Biomedical Devices using Machine Learning and Deep
Learning. 28. Prediction Modules for Biomedical Signal Processing. 29. Case
studies: Healthcare Monitoring Systems.
Introduction to Green and Red Artificial Intelligence. 2. Impact of
Artificial Intelligence Techniques on Green Applications. 3. Tools for
Artificial Intelligence in Green Applications. 4. Artificial Intelligence
for Human-Computer Interfaces. Part 2: Green Electronic Technology. 5.
Green Communication Technologies and Protocols. 6. Green Communication
Network Design and Implementation for Internet of Things Ecosystem. 7.
Smart Portable and Intelligent Internet of Things Enabled System for Green
Applications. 8. Green Computing in Network Security. 9. Artificial
Intelligence Models for Remote Sensing Applications. Part 3: Green Energy
Technology. 10. Energy Efficiency Models of Artificial Systems. 11.
Artificial Intelligence for Energy Storage Systems. 12. Smart Energy
Harvesting/Charging and Power Management Techniques using Machine Learning.
13. Renewable Energy Monitoring and Forecast based on Intelligent Data
Analysis. 14. Case Study on Artificial Intelligence Integration with Green
Energy Generation. Part 4: Green Environmental Solutions. 15. Green
Artificial Intelligence: Biodegradable and Biocompatible Materials. 16.
Artificial Intelligence in Nanotechnology for Green Applications. 17.
Virtually Going Green: The Role of Artificial Intelligence in Reducing
Pollution and Toxicity. 18. Prediction Models for Carbon Emission and
Sequestration. 19. Prediction Models for Environment Health. 20.
Predictions Models for Climate Change or Natural Disaster. 21. Air
Pollution Control. 22. Water Security and Ocean Technology. 23. Case Study:
Maintenance of Water Quality in Different Geographic Locations. Part 5:
Green Healthcare. 24. Digital Health Solutions with Bionic Devices. 25.
Smart Biomaterials. 26. Remote Health Monitoring and Telehealth. 27.
Optimization of Biomedical Devices using Machine Learning and Deep
Learning. 28. Prediction Modules for Biomedical Signal Processing. 29. Case
studies: Healthcare Monitoring Systems.
Part 1: Introduction to Artificial Intelligence in Green Technology. 1.
Introduction to Green and Red Artificial Intelligence. 2. Impact of
Artificial Intelligence Techniques on Green Applications. 3. Tools for
Artificial Intelligence in Green Applications. 4. Artificial Intelligence
for Human-Computer Interfaces. Part 2: Green Electronic Technology. 5.
Green Communication Technologies and Protocols. 6. Green Communication
Network Design and Implementation for Internet of Things Ecosystem. 7.
Smart Portable and Intelligent Internet of Things Enabled System for Green
Applications. 8. Green Computing in Network Security. 9. Artificial
Intelligence Models for Remote Sensing Applications. Part 3: Green Energy
Technology. 10. Energy Efficiency Models of Artificial Systems. 11.
Artificial Intelligence for Energy Storage Systems. 12. Smart Energy
Harvesting/Charging and Power Management Techniques using Machine Learning.
13. Renewable Energy Monitoring and Forecast based on Intelligent Data
Analysis. 14. Case Study on Artificial Intelligence Integration with Green
Energy Generation. Part 4: Green Environmental Solutions. 15. Green
Artificial Intelligence: Biodegradable and Biocompatible Materials. 16.
Artificial Intelligence in Nanotechnology for Green Applications. 17.
Virtually Going Green: The Role of Artificial Intelligence in Reducing
Pollution and Toxicity. 18. Prediction Models for Carbon Emission and
Sequestration. 19. Prediction Models for Environment Health. 20.
Predictions Models for Climate Change or Natural Disaster. 21. Air
Pollution Control. 22. Water Security and Ocean Technology. 23. Case Study:
Maintenance of Water Quality in Different Geographic Locations. Part 5:
Green Healthcare. 24. Digital Health Solutions with Bionic Devices. 25.
Smart Biomaterials. 26. Remote Health Monitoring and Telehealth. 27.
Optimization of Biomedical Devices using Machine Learning and Deep
Learning. 28. Prediction Modules for Biomedical Signal Processing. 29. Case
studies: Healthcare Monitoring Systems.
Introduction to Green and Red Artificial Intelligence. 2. Impact of
Artificial Intelligence Techniques on Green Applications. 3. Tools for
Artificial Intelligence in Green Applications. 4. Artificial Intelligence
for Human-Computer Interfaces. Part 2: Green Electronic Technology. 5.
Green Communication Technologies and Protocols. 6. Green Communication
Network Design and Implementation for Internet of Things Ecosystem. 7.
Smart Portable and Intelligent Internet of Things Enabled System for Green
Applications. 8. Green Computing in Network Security. 9. Artificial
Intelligence Models for Remote Sensing Applications. Part 3: Green Energy
Technology. 10. Energy Efficiency Models of Artificial Systems. 11.
Artificial Intelligence for Energy Storage Systems. 12. Smart Energy
Harvesting/Charging and Power Management Techniques using Machine Learning.
13. Renewable Energy Monitoring and Forecast based on Intelligent Data
Analysis. 14. Case Study on Artificial Intelligence Integration with Green
Energy Generation. Part 4: Green Environmental Solutions. 15. Green
Artificial Intelligence: Biodegradable and Biocompatible Materials. 16.
Artificial Intelligence in Nanotechnology for Green Applications. 17.
Virtually Going Green: The Role of Artificial Intelligence in Reducing
Pollution and Toxicity. 18. Prediction Models for Carbon Emission and
Sequestration. 19. Prediction Models for Environment Health. 20.
Predictions Models for Climate Change or Natural Disaster. 21. Air
Pollution Control. 22. Water Security and Ocean Technology. 23. Case Study:
Maintenance of Water Quality in Different Geographic Locations. Part 5:
Green Healthcare. 24. Digital Health Solutions with Bionic Devices. 25.
Smart Biomaterials. 26. Remote Health Monitoring and Telehealth. 27.
Optimization of Biomedical Devices using Machine Learning and Deep
Learning. 28. Prediction Modules for Biomedical Signal Processing. 29. Case
studies: Healthcare Monitoring Systems.