Deep Learning and Edge Computing for Internet of Things
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The evolution of 5G and Internet of Things (IoT) technologies is leading to ubiquitous connections between humans and their environment, such as autopilot transportation, mobile e-commerce, unmanned vehicles, and healthcare applications, bringing revolutionary changes to our daily lives. Moreover, the computing environment results in the requirement for support of an increasing range of functionality: multi-sensory data processing and analysis, complex systems control strategies, and, ultimately, artificial intelligence. After several years of development, edge computing for deep learning has ...
The evolution of 5G and Internet of Things (IoT) technologies is leading to ubiquitous connections between humans and their environment, such as autopilot transportation, mobile e-commerce, unmanned vehicles, and healthcare applications, bringing revolutionary changes to our daily lives. Moreover, the computing environment results in the requirement for support of an increasing range of functionality: multi-sensory data processing and analysis, complex systems control strategies, and, ultimately, artificial intelligence. After several years of development, edge computing for deep learning has shown incomparable practical value in the IoT environment. Pushing computing resources to the edge in closer proximity to devices enables low-latency service delivery for both safety and applications. This Special Issue, "Deep Learning and Edge Computing for Internet of Things", addresses existing awareness of the surrounding environment and support for services in the advanced development of smart scheduling, privacy protection, and environment-aware ability globally. It includes eleven peer-reviewed papers that focus on deep learning and edge computing for the Internet of Things.
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