Edge Machine Learning

Edge machine learning (Edge ML) focuses on performing machine learning tasks directly on resource-constrained devices, prioritizing low latency, reduced energy consumption, and data privacy. Current research emphasizes model compression techniques like pruning and quantization, along with efficient algorithms for data stream classification and robust monitoring of data quality in decentralized environments. This field is crucial for enabling intelligent applications in IoT devices and other edge deployments, impacting areas such as fraud detection, autonomous systems, and personalized healthcare.