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TinyML algorithms for Big Data Management in large-scale IoT systems
In the context of the Internet of Things (IoT), Tiny Machine Learning (TinyML) and Big Data,
enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive …
enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive …
Application of machine learning to leakage detection of fluid pipelines in recent years: A review and prospect
Pipelines are the most efficient means of transporting water, oil, gas, and other fluids.
Nevertheless, the occurrence of pipeline leaks can lead to significant resource wastage and …
Nevertheless, the occurrence of pipeline leaks can lead to significant resource wastage and …
Tiny-machine-learning-based supply canal surface condition monitoring
The South-to-North Water Diversion Project in China is an extensive inter-basin water
transfer project, for which ensuring the safe operation and maintenance of infrastructure …
transfer project, for which ensuring the safe operation and maintenance of infrastructure …
Water leakage classification with acceleration, pressure, and acoustic data: Leveraging the wavelet scattering transform, unimodal classifiers, and late fusion
EA Martinez-Ríos, D Barrientos, R Bustamante - IEEE Access, 2024 - ieeexplore.ieee.org
Early detection of water leakages is crucial due to their social, environmental, and economic
impacts. In this regard, machine learning (ML) algorithms have been proposed in the …
impacts. In this regard, machine learning (ML) algorithms have been proposed in the …
[HTML][HTML] Green IoT Event Detection for Carbon-Emission Monitoring in Sensor Networks
This research addresses the intersection of low-power microcontroller technology and
binary classification of events in the context of carbon-emission reduction. The study …
binary classification of events in the context of carbon-emission reduction. The study …
TinyML4D: Scaling Embedded Machine Learning Education in the Develo** World
Embedded machine learning (ML) on low-power devices, also known as" TinyML," enables
intelligent applications on accessible hardware and fosters collaboration across disciplines …
intelligent applications on accessible hardware and fosters collaboration across disciplines …
TinyChirp: Bird song recognition using TinyML models on low-power wireless acoustic sensors
Monitoring biodiversity at scale is challenging. De-tecting and identifying species in fine
grained taxonomies requires highly accurate machine learning (ML) methods. Training such …
grained taxonomies requires highly accurate machine learning (ML) methods. Training such …
[HTML][HTML] Gas Leakage Detection Using Tiny Machine Learning
Gas leakage detection is a critical concern in both industrial and residential settings, where
real-time systems are essential for quickly identifying potential hazards and preventing …
real-time systems are essential for quickly identifying potential hazards and preventing …
Parameter Selection of Generalized Morse Wavelets for Water Leakage Classification
Water leakage detection in water distribution networks is crucial to mitigating water scarcity.
Machine learning algorithms have been utilized to generate models that detect water …
Machine learning algorithms have been utilized to generate models that detect water …
IoT Based Gas Pipeline Monitoring System
Gas leakage have the potential to lead to significant incidents that can result in both physical
harm to individuals and financial setbacks. The rise of IoT (Internet of Things) technology …
harm to individuals and financial setbacks. The rise of IoT (Internet of Things) technology …