Eduard Babulak – författare

This book explores the role of artificial Intelligence in Telemedicine. It explains the concepts through the detailed study and processing of biosignals, physiological parameters, and medical images. The book focuses on computational algorithms in telemedicine for the processing of biosignals, physiological parameters, and medical Images. The book is presented in two section. The first section presents the role of computational algorithms in the processing of biosignal and medical images for disease diagnosis and treatment planning. Noise removal in ECG signal using an improved adaptive learning approach, classification of ECG signals using CNN for cardiac arrhythmia detection, EEG signal analysis for stroke detection, and EMG signal analysis for gesture classification were discussed in this section. Application of CNN in pertussis Diagnosis by temperature monitoring, physician handwriting recognition using deep learning model, melanoma detection using ABCD parameters, and transfer learning enabled heuristic approach for pneumonia detection was also discussed in this section The second section focus on the role of IoT and artificial intelligence in the healthcare sector. IoT in smart health care and applications of artificial intelligence in disease diagnosis and prediction was discussed in this section. The importance of 5G/6G in the pandemic scenario for telemedicine applications, wireless capsule endoscopy image compression, leukemia detection from the microscopic cell images, and genomic signal processing using numerical mapping techniques was also discussed in this section. This book can be used by a wide range of users including students, research scholars, faculty, and practitioners in the field of engineering for applications in biomedical signal, image analysis, and diagnosis.

This book explores the role of artificial Intelligence in Telemedicine. It explains the concepts through the detailed study and processing of biosignals, physiological parameters, and medical images. The book focuses on computational algorithms in telemedicine for the processing of biosignals, physiological parameters, and medical Images. The book is presented in two section. The first section presents the role of computational algorithms in the processing of biosignal and medical images for disease diagnosis and treatment planning. Noise removal in ECG signal using an improved adaptive learning approach, classification of ECG signals using CNN for cardiac arrhythmia detection, EEG signal analysis for stroke detection, and EMG signal analysis for gesture classification were discussed in this section. Application of CNN in pertussis Diagnosis by temperature monitoring, physician handwriting recognition using deep learning model, melanoma detection using ABCD parameters, and transfer learning enabled heuristic approach for pneumonia detection was also discussed in this section The second section focus on the role of IoT and artificial intelligence in the healthcare sector. IoT in smart health care and applications of artificial intelligence in disease diagnosis and prediction was discussed in this section. The importance of 5G/6G in the pandemic scenario for telemedicine applications, wireless capsule endoscopy image compression, leukemia detection from the microscopic cell images, and genomic signal processing using numerical mapping techniques was also discussed in this section. This book can be used by a wide range of users including students, research scholars, faculty, and practitioners in the field of engineering for applications in biomedical signal, image analysis, and diagnosis.

This book offers insights into how modern technologies are transforming agriculture with a focus on their effects in aiding sustainability. It explores the current applications of technologies such as AI, IoT, and machine learning, and their impact on improving crop yield, resource efficiency, and environmental impact. Through practical examples and case studies, it demonstrates how these technologies can address challenges in agriculture and enhance operational efficiency. Key Features:Analysis of how IoT devices and sensor networks are used for real-time monitoring of farm operations, soil conditions, and weather patterns.Studies emerging technologies like machine vision, predictive modelling, and natural language processing, for tasks such as crop monitoring and pest detection.Detailed discussion on machine learning algorithms, including supervised, unsupervised, and reinforcement learning, tailored for agricultural applications.Insights into how AI, IoT, and machine learning optimize resource use, improve crop yield and quality, and enhance sustainability.Case studies to highlight real-life examples from crop management to livestock and water conservation.Smart Agriculture for Sustainable Practices is for researchers, professionals, and policymakers interested in leveraging technology for sustainable agricultural practices.

color: black;">This book constitutes the refereed proceedings of the Second International Conference on Emerging Wireless Technologies and Sciences, ICEWTS 2024, held in Uttarakhand, India, during October 6–7, 2024. The 8 full papers and 4 short papers included in this book were carefully reviewed and selected from 430 submissions.