The Unstoppable Rise of Edge Computing: Revolutionizing IoT and Deep Learning
The evolution of 5G and Internet of Things (IoT) technologies is leading to ubiquitous connections among humans and their environment, revolutionizing various industries and applications such as autopilot transportation, mobile e-commerce, unmanned vehicles, and healthcare. These advancements have brought about revolutionary changes to our daily lives. However, as the computing environment becomes more complex, there is a growing need for edge computing to support an increasing range of functionality.
Edge computing is a decentralized computing approach that pushes computing resources closer to devices, enabling low-latency service delivery for both safety and applications. In recent years, edge computing for deep learning has proven its practical value in the IoT environment. It has the ability to process and analyze multi-sensory data, implement complex system control strategies, and even facilitate artificial intelligence. The benefits of edge computing for deep learning are undeniable.
Despite the progress made, edge computing still has untapped potential for deep learning. Systems should not only focus on leveraging awareness of the surrounding environment but also prioritize edge-edge intelligence collaboration and edge-cloud communication. Additionally, computation systems should provide more support for services like edge AI to optimize the computing process. This would include smart scheduling, privacy protection, and environment-aware ability, among other features.
The potential of edge computing in the IoT environment is vast, which is why a Special Issue has been dedicated to exploring recent advances in edge computing technologies. The topics of interest for this issue include edge-edge intelligence collaboration, edge-cloud communication, smart scheduling, privacy protection, and environment-aware ability. Through this collection of research articles, review articles, and short communications, experts in the field aim to shed light on the future of edge computing and its impact on the ubiquitous IoT environment.
Manuscripts can be submitted until the deadline through the online submission form on the journal’s website. All submissions will undergo a thorough peer-review process. Accepted papers will be published continuously in the journal and listed on the special issue website.
To ensure an optimized reading experience, submitted manuscripts should be well formatted and written in clear, concise English. Authors may choose to avail of MDPI’s English editing service for assistance. Furthermore, it is crucial that submitted papers have not been previously published or under consideration for publication elsewhere, except for conference proceedings papers.
Applied Sciences, the journal hosting this Special Issue, is an internationally recognized peer-reviewed open access semimonthly journal published by MDPI. With the Article Processing Charge (APC) set at 2300 CHF (Swiss Francs), authors can benefit from the wide reach and accessibility of the journal.
In conclusion, edge computing is set to revolutionize the IoT environment and bring about groundbreaking changes in various industries. With its ability to provide low-latency service delivery, process multi-sensory data, and optimize the computing process, edge computing for deep learning has proven its value. The Special Issue aims to shed light on recent advances in edge computing technologies and explore its untapped potential. Researchers, scientists, and industry experts are encouraged to contribute their insights and findings to further enhance the understanding and implementation of edge computing in the IoT environment.
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