بِسْمِ اللَّهِ الرَّحْمَنِ الرَّحِيمِ

دانلود کتاب هوش مصنوعی لبه کاربردی: مفاهیم، بسترها، و موارد استفاده در صنعت

Applied Edge AI: Concepts, Platforms, and Industry Use Cases, R. I. Minu, G. Nagarajan, Pethuru Raj Chelliah, 0367702363, 9780367702366, 978-0367702366

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English | 2022 | PDF | زمان تحویل: کمتر از 8 ساعت

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The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance processors, etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations. Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases

FEATURES
The opportunities and benefits of intelligent edge computing
Edge architecture and infrastructure
AI-enhanced analytics in an edge environment
Encryption for securing information
An Edge AI system programmed with Tiny Machine learning algorithms for decision making
An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge
Ambient intelligence in healthcare services and in development of consumer electronic systems
Smart manufacturing of unmanned aerial vehicles (UAVs)
AI, edge computing, and blockchain in systems for environmental protection
Case studies presenting the potential of leveraging AI in 5G wireless communication