A 0.8 mw tinyml-based pdm-to-pcm conversion for in-sensor kws applications
P Vitolo, R Liguori, L Di Benedetto, A Rubino… - Annual Meeting of the …, 2022 - Springer
This paper proposes an ultra-low-power hardware architecture of a tiny machine learning
(tinyML)-based conversion from Pulse Density Modulation (PDM) to Pulse Code Modulation …
(tinyML)-based conversion from Pulse Density Modulation (PDM) to Pulse Code Modulation …
TwinSync: A Digital Twin Synchronization Protocol for Bandwidth-Limited IoT Applications
Digital Twins are evolving as a key component in modern systems with diverse applications
like remote prognostics, optimizing run-time operation, anomaly detection, and more. The …
like remote prognostics, optimizing run-time operation, anomaly detection, and more. The …
RF-based Energy Harvesting: Nonlinear Models, Applications and Challenges
R Jiang - arXiv preprint arXiv:2405.04976, 2024 - arxiv.org
So far, various aspects associated with wireless energy harvesting (EH) have been
investigated from diverse perspectives, including energy sources and models, usage …
investigated from diverse perspectives, including energy sources and models, usage …
SDCL: A Framework for Secure, Distributed, and Collaborative Learning in Smart Grids
AA Abdellatif, K Shaban… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The future of electric grids is undergoing a remarkable transformation driven by the
increasing adoption of emerging technologies, notably Artificial Intelligence (AI) and …
increasing adoption of emerging technologies, notably Artificial Intelligence (AI) and …
AI-based framework for Construction 4.0: A case study for structural health monitoring
Construction 4.0 is a revolutionary paradigm that leverages the power of artificial
intelligence to facilitate the smart interaction between cyber-physical systems and digital …
intelligence to facilitate the smart interaction between cyber-physical systems and digital …
PANCODE: Multilevel Partitioning of Neural Networks for Constrained Internet-of-Things Devices
The increasing number of Internet-of-Things (IoT) devices will generate unprecedented data
in the upcoming years. Fog computing may prevent the saturation of the network …
in the upcoming years. Fog computing may prevent the saturation of the network …
[HTML][HTML] A review of artificial intelligence applications in high-speed railway systems
In recent years, the global surge of High-speed Railway (HSR) revolutionized ground
transportation, providing secure, comfortable, and punctual services. The next-gen HSR …
transportation, providing secure, comfortable, and punctual services. The next-gen HSR …
Dynamic Pruning for Distributed Inference via Explainable AI: A Healthcare Use Case
The healthcare sector has undergone a significant transformation with the widespread
adoption of Deep Neural Networks (DNN). However, due to privacy constraints and stringent …
adoption of Deep Neural Networks (DNN). However, due to privacy constraints and stringent …
Low-Complexity and High-Performance Combiners for Over the Air Computing
K Ando, GTF de Abreu - 2023 IEEE 9th International Workshop …, 2023 - ieeexplore.ieee.org
We consider the design of successive convex approx-imation (SCA)-based mean square
error (MSE) minimization combiners for over-the-air-computation (AirComp) schemes op …
error (MSE) minimization combiners for over-the-air-computation (AirComp) schemes op …
Survey and Enhancements on Deploying LSTM Recurrent Neural Networks on Embedded Systems
G Abib, F Castel, N Satouri, H Afifi… - ICC 2023-IEEE …, 2023 - ieeexplore.ieee.org
The real implementation of a recurrent neural network (RNN) in a low complexity IoT device
is evaluated in order to predict the time series of power consumption in tertiary buildings …
is evaluated in order to predict the time series of power consumption in tertiary buildings …