AI and Edge Computing: Synergistic Approaches for Real-time Data Processing in Cloud Environments
Abstract
The application of AI integrated with edge computing systems and cloud solutions in data processing and decision-making processes rapidly evolves to enhance real-time decision-making across several industries. The following article explains the relationship between these technologies and examines the interests and benefits of their integration. While edge computing gives enhanced information examination because it examines information at the actual source and with a lower latency rate, cloud computing is indispensable for training complex deep machine learning models and dealing with large volumes of data. In the real world, smart cities, healthcare, & industrial IoT are some areas that show this integration's value. Even so, the following challenges need to be solved to use these technologies better: complexity, security, and interoperability. Future development trends, including edge AI growth, the effects of 5G, and more attention paid to data security and intelligence, will also contribute to the evolution of AI with edge and cloud systems. In this context, more organizations require capturing and dissection of these dynamics to devise suitable strategies for managing technological change in the future to pry open the possibility of innovation and productivity.
Keywords
Artificial Intelligence, Edge Computing, Cloud Computing, Real-Time Data Processing, Smart Cities, Industrial IoT, Data Privacy, Security, 5G Technology, Automation.
Citations
IRE Journals:
Purushotham Reddy
"AI and Edge Computing: Synergistic Approaches for Real-time Data Processing in Cloud Environments" Iconic Research And Engineering Journals Volume 6 Issue 8 2023 Page 292-301
IEEE:
Purushotham Reddy
"AI and Edge Computing: Synergistic Approaches for Real-time Data Processing in Cloud Environments" Iconic Research And Engineering Journals, 6(8)
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