Intelligent Technologies for Research and Engineering
This volume explores diverse applications for automated machine learning and predictive analytics. The content provides use cases for machine learning in different industries such as healthcare, agriculture, cybersecurity, computing and transportation. Key highlights of this volume include topics on engineering for underwater navigation, and computer vision for healthcare and biometric applications. Chapters 1-4 delve into innovative signal detection, biometric authentication, underwater AUV localization, and COVID-19 face mask detection. Chapters 5-9 focus on wireless pH sensing, differential pattern identification, economic considerations in off-grid hybrid power, high optimization of image transmission, and ANN-based IoT-bot traffic detection. Chapters 10-12 cover mixed-signal VLSI design, pre-placement 3D floor planning, and bio-mimic robotic fish. Finally, Chapters 13 and 14 explore underwater robotic fish and IoT-based automatic irrigation systems, providing a comprehensive overview of cutting-edge technological advancements. The book is a resource for academics, researchers, educators and professionals in the technology sector who want to learn about current trends in intelligent technologies.This volume explores diverse applications for automated machine learning and predictive analytics. The content provides use cases for machine learning in different industries such as healthcare, agriculture, cybersecurity, computing and transportation. Key highlights of this volume include topics on engineering for underwater navigation, and computer vision for healthcare and biometric applications. Chapters 1-4 delve into innovative signal detection, biometric authentication, underwater AUV localization, and COVID-19 face mask detection. Chapters 5-9 focus on wireless pH sensing, differential pattern identification, economic considerations in off-grid hybrid power, high optimization of image transmission, and ANN-based IoT-bot traffic detection. Chapters 10-12 cover mixed-signal VLSI design, pre-placement 3D floor planning, and bio-mimic robotic fish. Finally, Chapters 13 and 14 explore underwater robotic fish and IoT-based automatic irrigation systems, providing a comprehensive overview of cutting-edge technological advancements. The book is a resource for academics, researchers, educators and professionals in the technology sector who want to learn about current trends in intelligent technologies.
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This volume explores diverse applications for automated machine learning and predictive analytics. The content provides use cases for machine learning in different industries such as healthcare, agric
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S. Kannadhasan
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