TinyML for Acoustic Anomaly Detection in IoT Sensor Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Almaini, Amar, Folz, Jakob, Ashour, Ghadeer |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TinyML-Enabled IoT for Sustainable Precision Irrigation
by: Taueatsoala, Kamogelo, et al.
Published: (2026)
by: Taueatsoala, Kamogelo, et al.
Published: (2026)
DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
by: Han, Lixiang, et al.
Published: (2024)
by: Han, Lixiang, et al.
Published: (2024)
U-TOE: Universal TinyML On-board Evaluation Toolkit for Low-Power IoT
by: Huang, Zhaolan, et al.
Published: (2023)
by: Huang, Zhaolan, et al.
Published: (2023)
TinyChirp: Bird Song Recognition Using TinyML Models on Low-power Wireless Acoustic Sensors
by: Huang, Zhaolan, et al.
Published: (2024)
by: Huang, Zhaolan, et al.
Published: (2024)
Simulating Battery-Powered TinyML Systems Optimised using Reinforcement Learning in Image-Based Anomaly Detection
by: Ping, Jared M., et al.
Published: (2024)
by: Ping, Jared M., et al.
Published: (2024)
MLonMCU: TinyML Benchmarking with Fast Retargeting
by: van Kempen, Philipp, et al.
Published: (2023)
by: van Kempen, Philipp, et al.
Published: (2023)
TinySV: Speaker Verification in TinyML with On-device Learning
by: Pavan, Massimo, et al.
Published: (2024)
by: Pavan, Massimo, et al.
Published: (2024)
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
by: Dehrouyeh, Fatemeh, et al.
Published: (2025)
by: Dehrouyeh, Fatemeh, et al.
Published: (2025)
Accelerating TinyML Inference on Microcontrollers through Approximate Kernels
by: Armeniakos, Giorgos, et al.
Published: (2024)
by: Armeniakos, Giorgos, et al.
Published: (2024)
K-Means Based TinyML Anomaly Detection and Distributed Model Reuse via the Distributed Internet of Learning (DIoL)
by: Albaiz, Abdulrahman, et al.
Published: (2026)
by: Albaiz, Abdulrahman, et al.
Published: (2026)
Once-for-All Channel Mixers (HYPERTINYPW): Generative Compression for TinyML
by: Shaalan, Yassien
Published: (2026)
by: Shaalan, Yassien
Published: (2026)
Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data
by: Albaiz, Abdulrahman, et al.
Published: (2026)
by: Albaiz, Abdulrahman, et al.
Published: (2026)
On The Dynamic Ensemble Selection for TinyML-based Systems -- a Preliminary Study
by: Puslecki, Tobiasz, et al.
Published: (2025)
by: Puslecki, Tobiasz, et al.
Published: (2025)
MicroFlow: An Efficient Rust-Based Inference Engine for TinyML
by: Carnelos, Matteo, et al.
Published: (2024)
by: Carnelos, Matteo, et al.
Published: (2024)
Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?
by: Zeinaty, Christophe El, et al.
Published: (2025)
by: Zeinaty, Christophe El, et al.
Published: (2025)
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
by: Deutel, Mark, et al.
Published: (2023)
by: Deutel, Mark, et al.
Published: (2023)
Dendron: Enhancing Human Activity Recognition with On-Device TinyML Learning
by: Shalby, Hazem Hesham Yousef, et al.
Published: (2025)
by: Shalby, Hazem Hesham Yousef, et al.
Published: (2025)
msf-CNN: Patch-based Multi-Stage Fusion with Convolutional Neural Networks for TinyML
by: Huang, Zhaolan, et al.
Published: (2025)
by: Huang, Zhaolan, et al.
Published: (2025)
Hardware-efficient tractable probabilistic inference for TinyML Neurosymbolic AI applications
by: Leslin, Jelin, et al.
Published: (2025)
by: Leslin, Jelin, et al.
Published: (2025)
Benchmarking Energy and Latency in TinyML: A Novel Method for Resource-Constrained AI
by: Bartoli, Pietro, et al.
Published: (2025)
by: Bartoli, Pietro, et al.
Published: (2025)
On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Case
by: Dehrouyeh, Fatemeh, et al.
Published: (2024)
by: Dehrouyeh, Fatemeh, et al.
Published: (2024)
TinyML Security: Exploring Vulnerabilities in Resource-Constrained Machine Learning Systems
by: Huckelberry, Jacob, et al.
Published: (2024)
by: Huckelberry, Jacob, et al.
Published: (2024)
On-device Online Learning and Semantic Management of TinyML Systems
by: Ren, Haoyu, et al.
Published: (2024)
by: Ren, Haoyu, et al.
Published: (2024)
TinyTNAS: GPU-Free, Time-Bound, Hardware-Aware Neural Architecture Search for TinyML Time Series Classification
by: Saha, Bidyut, et al.
Published: (2024)
by: Saha, Bidyut, et al.
Published: (2024)
Optimizing TinyML: The Impact of Reduced Data Acquisition Rates for Time Series Classification on Microcontrollers
by: Samanta, Riya, et al.
Published: (2024)
by: Samanta, Riya, et al.
Published: (2024)
Integration of TinyML and LargeML: A Survey of 6G and Beyond
by: Vu, Thai-Hoc, et al.
Published: (2025)
by: Vu, Thai-Hoc, et al.
Published: (2025)
Optimizing Split Learning Latency in TinyML-Based IoT Systems
by: Jenhani, Zied, et al.
Published: (2025)
by: Jenhani, Zied, et al.
Published: (2025)
Consolidating TinyML Lifecycle with Large Language Models: Reality, Illusion, or Opportunity?
by: Wu, Guanghan, et al.
Published: (2025)
by: Wu, Guanghan, et al.
Published: (2025)
Agentic TinyML for Intent-aware Handover in 6G Wireless Networks
by: Saleh, Alaa, et al.
Published: (2025)
by: Saleh, Alaa, et al.
Published: (2025)
What changes after deployment? A survey on On-device Learning in TinyML
by: Pavan, Massimo, et al.
Published: (2026)
by: Pavan, Massimo, et al.
Published: (2026)
A Survey of TinyML Applications in Beekeeping for Hive Monitoring and Management
by: Sucipto, Willy, et al.
Published: (2025)
by: Sucipto, Willy, et al.
Published: (2025)
Federated Structured Sparse PCA for Anomaly Detection in IoT Networks
by: Huang, Chenyi, et al.
Published: (2025)
by: Huang, Chenyi, et al.
Published: (2025)
BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables
by: Samakovlis, Dimitrios, et al.
Published: (2024)
by: Samakovlis, Dimitrios, et al.
Published: (2024)
Optimising TinyML with Quantization and Distillation of Transformer and Mamba Models for Indoor Localisation on Edge Devices
by: Suwannaphong, Thanaphon, et al.
Published: (2024)
by: Suwannaphong, Thanaphon, et al.
Published: (2024)
SNAP-UQ: Self-supervised Next-Activation Prediction for Single-Pass Uncertainty in TinyML
by: Lamaakal, Ismail, et al.
Published: (2025)
by: Lamaakal, Ismail, et al.
Published: (2025)
Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning
by: Bao, Ziyuan, et al.
Published: (2025)
by: Bao, Ziyuan, et al.
Published: (2025)
Toward Attention-based TinyML: A Heterogeneous Accelerated Architecture and Automated Deployment Flow
by: Wiese, Philip, et al.
Published: (2024)
by: Wiese, Philip, et al.
Published: (2024)
QUTE: Quantifying Uncertainty in TinyML with Early-exit-assisted ensembles for model-monitoring
by: Ghanathe, Nikhil P, et al.
Published: (2024)
by: Ghanathe, Nikhil P, et al.
Published: (2024)
Hybrid Convolution and Vision Transformer NAS Search Space for TinyML Image Classification
by: Djajapermana, Mikhael, et al.
Published: (2025)
by: Djajapermana, Mikhael, et al.
Published: (2025)
IGADA-IoT: IoT Sensor Energy Optimization in Wireless Sensor Networks Driven by Automatic Data Augmentation
by: Sun, Mingchun, et al.
Published: (2026)
by: Sun, Mingchun, et al.
Published: (2026)
Similar Items
-
TinyML-Enabled IoT for Sustainable Precision Irrigation
by: Taueatsoala, Kamogelo, et al.
Published: (2026) -
DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
by: Han, Lixiang, et al.
Published: (2024) -
U-TOE: Universal TinyML On-board Evaluation Toolkit for Low-Power IoT
by: Huang, Zhaolan, et al.
Published: (2023) -
TinyChirp: Bird Song Recognition Using TinyML Models on Low-power Wireless Acoustic Sensors
by: Huang, Zhaolan, et al.
Published: (2024) -
Simulating Battery-Powered TinyML Systems Optimised using Reinforcement Learning in Image-Based Anomaly Detection
by: Ping, Jared M., et al.
Published: (2024)