Empowering AI Applications in Smart Life and EnvironmentКНИГИ » ПРОГРАММИНГ
Название: Empowering AI Applications in Smart Life and Environment Автор: Nour Eldeen Mahmoud Khalifa, Mohamed Hamed N. Taha Издательство: Springer Год: 2025 Страниц: 250 Язык: английский Формат: pdf (true), epub Размер: 41.7 MB
"Empowering AI Applications in Smart Life and Environment" provides a comprehensive exploration of how Artificial Intelligence (AI) can transform smart environments and contribute to sustainable living. It investigates the integrating of AI with visual, audio, and haptic devices that can revolutionize energy optimization, intelligent transportation, healthcare management, smart farming, and smart homes. The book aims to highlight the latest research and developments in AI applications that drive the enhancement of smart environments and sustainable life.
The chapters are divided into two broad parts, the first part of this book discusses "Artificial Intelligence in Smart Systems, Environments and Security" inclusive of, but not limited to AI-based energy efficiency, object detection, defect detection in smart infrastructure, AI-driven IoT platforms, and strategies of Machine Learning for cybersecurity. The second part entitled "Artificial Intelligence in Smart Healthcare and Sustainability" shows how AI helps in the multi-class diagnosis of skin diseases, elderly care, and enhancement of post-consumer plastics recycling. This book is an intense exercise in learning about the various ways AI can make environments smarter, sustainable, and secure.
AI is the backbone of new developments in smart technological applications like intelligent manufacturing. Within AI as currently practiced, there are two primary subdivisions: Machine Learning (ML) and Deep Learning (DL), whereby both are also important to defend against potential cybersecurity risks. When it comes to cybersecurity threats and cyber-attack incidents, they are the biggest cybersecurity risk, because automation allows cybercriminals to reach a breadth and scale never seen before. ML focuses on classification and regression, based on previously learned features from the training data. In contrast DL based on learning from data. Let’s assume an image that can be described in a variety of ways, such as a vector of each pixel intensity value, or more abstract as a series of edges, a region of a particular shape, or the like. Furthermore, AI, and hence ML and DL, can analyze large amounts of data in almost less time, a capability when it comes to a cybersecurity risk problem, to detect cybersecurity risks, like malware, phishing, and others. On one hand, in case of a ML application, which is a pattern matching approach, multiple factors across multiple records can be analyzed, which can result in the conclusion that an outlier exist, or an anomalous pattern is detected, or another cybersecurity attack scenario has taken access to the system under investigation.
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Internet of Things for Smart Environments Название: Internet of Things for Smart Environments Автор: Goncalo Marques, Alfonso Gonzalez-Briones Издательство: Springer-EAI Год: 2023 Страниц:...
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