Edge Machine Learning for AI-Enabled IoT Devices: A Review
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Abstract
In a few years, the world will be populated by billions of connected devices that will be placed in our homes, cities, vehicles, and industries. Devices with limited resources will interact with the surrounding environment and users. Many of these devices will be based on machine learning models to decode meaning and behavior behind sensors' data, to implement accurate predictions and make decisions. The bottleneck will be the high level of connected things that could congest the network. Hence, the need to incorporate intelligence on end devices using machine learning algorithms. Deploying machine learning on such edge devices improves the network congestion by allowing computations to be performed close to…
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3Topics & keywords
Topics
Keywords
- Computer science
- Edge device
- Bottleneck
- Artificial intelligence
- Enhanced Data Rates for GSM Evolution
- Machine learning
- Edge computing
- The Internet
UN Sustainable Development Goals
- Sustainable cities and communities
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