Results 31 to 40 of about 793 (174)

GA‐ANN: An Efficient Hybrid Deep Learning Scheme for Network Intrusion Detection in IoT

SECURITY AND PRIVACY, Volume 9, Issue 4, July/August 2026.
ABSTRACT Intrusion detection systems (IDS) are critical to the security of the dynamic internet of things (IoT) environment. The integration of Artificial Intelligence (AI) into IDS has substantially improved network security. Particularly, deep learning techniques have shown strong potential in addressing IoT security challenges.
Naveed Ahmed, M. Siraj Rathore, Azhar Mahmood, Muhammad Daniyal, Md Asri Ngadi   +4 more
wiley   +1 more source

A TinyML Approach to Real-Time Snoring Detection in Resource-Constrained Wearables Devices

Engineering Proceedings
This study proposes a health monitoring system for snoring detection utilizing Tiny Machine Learning (TinyML) models, specifically designed for resource-constrained wearable Internet of Things (IoT) devices.
Timothy Malche, Sumegh Tharewal, Priti Maheshwary   +2 more
doaj   +1 more source

Empowering Electrochemical Biosensors with AI: Overcoming Interference for Precise Dopamine Detection in Complex Samples

Advanced Intelligent Systems, 2023
Two significant issues in biosensors that can't be solved by conventional analytical methods are selectivity among likely biological interfering molecules and background noise in clinical samples.
José Ilton de Oliveira Filho, Murilo Calil Faleiros, Daisy Camargo Ferreira, Veerappan Mani, Khaled Nabil Salama   +4 more
doaj   +1 more source

Real‐Time Data‐Driven Fault Diagnosis of Photovoltaic Arrays Using an Edge‐Server Machine‐Learning Framework

Energy Science &Engineering, Volume 14, Issue 6, Page 2961-2982, June 2026.
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan, Sowmya Ravichandran, Deepak Kumar Sinha, Chandran Ramakrishnan, Omar Almomani   +4 more
wiley   +1 more source

A Novel Active RFID and TinyML based system for livestock Localization in Pakistan

Sir Syed University Research Journal of Engineering and Technology
Localization of livestock is a vital component of good livestock management in Pakistan. This abstract describes a unique method for livestock localization in Pakistan that makes use of Active RFID technology and Tiny Machine Learning (TinyML ...
Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali   +3 more
doaj   +1 more source

Optimization and Benchmarking of Lightweight Neural Networks for Efficient Embedded AI Deployment

Engineering Reports, Volume 8, Issue 5, May 2026.
A hardware‐aware optimization and benchmarking framework for lightweight neural networks is presented for deployment on heterogeneous embedded platforms including CPU, GPU, TPU, and MCU architectures. Model compression techniques such as quantization, pruning, knowledge distillation, and mixed‐precision computation reduce inference latency, memory ...
Vidapankal Mohammad Fridous, Abhishek Agarwal, K. B. Bhaskar, V. Nandagopal, N. Sivakamasundari   +4 more
wiley   +1 more source

Comparing training window selection methods for prediction in non‐stationary time series

British Journal of Mathematical and Statistical Psychology, Volume 79, Issue 2, Page 341-361, May 2026.
Abstract The widespread adoption of smartphones creates the possibility to passively monitor everyday behaviour via sensors. Sensor data have been linked to moment‐to‐moment psychological symptoms and mood of individuals and thus could alleviate the burden associated with repeated measurement of symptoms.
Fridtjof Petersen, Jonas M. B. Haslbeck, Jorge N. Tendeiro, Anna M. Langener, Martien J. H. Kas, Dimitris Rizopoulos, Laura F. Bringmann   +6 more
wiley   +1 more source

A TinyDL Model for Gesture-Based Air Handwriting Arabic Numbers and Simple Arabic Letters Recognition

IEEE Access
The application of tiny machine learning (TinyML) in human-computer interaction is revolutionizing gesture recognition technologies. However, there remains a significant gap in the literature regarding the effective recognition of complex scripts, such ...
Ismail Lamaakal, Ibrahim Ouahbi, Khalid El Makkaoui, Yassine Maleh, Pawel Plawiak, Fahad Alblehai   +5 more
doaj   +1 more source

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki, Bassam Bachour Junior, Marcelo Mulato, José Ilton de Oliveira Filho   +3 more
wiley   +1 more source

XiNet: Efficient Neural Networks for tinyML

2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023
The recent interest in the edge-to-cloud continuum paradigm has emphasized the need for simple and scalable architectures to deliver optimal performance on computationally constrained devices. However, resource-efficient neural networks usually optimize for parameter count and thus use operators such as depthwise convolutions, which do not maximally ...
Alberto Ancilotto, Francesco Paissan, Elisabetta Farella   +2 more
openaire   +2 more sources