Edgesl: Edge-computing architecture on smart lighting control with distilled knn for optimum processing time
Our previous research applied a novel classification-integrated moving average (CIMA)
method, an intelligence method that improves the performance of passive infrared (PIR) …
method, an intelligence method that improves the performance of passive infrared (PIR) …
Subsample, Generate, and Stack Using the Spiral Discovery Method: A Framework for Autoregressive Data Compression and Augmentation
ÁB Csapó - IEEE Transactions on Systems, Man, and …, 2024 - ieeexplore.ieee.org
This article addresses the challenge of efficiently managing datasets of various sizes
through two key strategies: 1) dataset compression and 2) synthetic augmentation. This …
through two key strategies: 1) dataset compression and 2) synthetic augmentation. This …
[HTML][HTML] Low-Power Preprocessing System at MCU-Based Application Nodes for Reducing Data Transmission
Edge computing enables prompt responses in IoT environments, such as the operation of
autonomous vehicles and unmanned aerial vehicles. However, with the increase in sensor …
autonomous vehicles and unmanned aerial vehicles. However, with the increase in sensor …
Federated Learning in Mesh Networks
X Wang, Y Chen, OA Dobre - Artificial Intelligence for Future …, 2025 - Wiley Online Library
Federated learning, emphasizing decentralized machine learning without central data
aggregation, has expanded notably, attributed to its data privacy benefits and reduced …
aggregation, has expanded notably, attributed to its data privacy benefits and reduced …
Preprocessing at Application Nodes for Reduction of Data Transmission in Edge Computing
Existing edge computing collects data from applications and transmits it to edge nodes.
However, as the amount of data transmission increases, the network burden also increases …
However, as the amount of data transmission increases, the network burden also increases …