Results 91 to 100 of about 7,108,814 (163)

Scalable Sewer Fault Detection and Condition Assessment Using Embedded Machine Vision

Engineering Proceedings
Municipal sewer networks span across large areas in cities around the world and require regular inspection to identify structural failures, blockages, and other issues that pose public health risks.
Timothy Malche
doaj   +1 more source

Contactless Glucose Sensing Using Miniature mm-Wave Radar and Tiny Machine Learning

IEEE Journal of Microwaves
In this article, we present a contactless glucose sensing system called GlucoRadar, which leverages a miniature low-power mm-wave radar for data collection, data augmentation to boost the training data, and tiny machine learning (TinyML) for the ...
Reza Nikandish, Caroline Sheedy, Jiayu He, Ruth Crowe, Deeksha Rao   +4 more
doaj   +1 more source

Secure Tiny Machine Learning on Edge Devices: A Lightweight Dual Attestation Mechanism for Machine Learning

Future Internet
Emerging edge devices are transforming the Internet of Things (IoT) by enabling more responsive and efficient interactions between physical objects and digital networks.
Vlad-Eusebiu Baciu, An Braeken, Laurent Segers, Bruno da Silva   +3 more
doaj   +1 more source

Lightweight TinyML-Enhanced Task Offloading in VANETs for Next-Generation Intelligent Transportation Systems

IEEE Open Journal of the Communications Society
Vehicular Ad Hoc Networks (VANETs) face resource constraints, high node mobility, and stringent latency requirements, especially in safety-critical applications such as collision avoidance, path planning, and emergency braking.
Muhammad Ali, Tariq Qayyum, Asadullah Tariq, Zouheir Trabelsi, Irfan Ud Din, Shabir Ahmed   +5 more
doaj   +1 more source

Targeted Active Learning for Bayesian Decision-Making

Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way.
Kaski, Samuel, Tiulpin, Aleksei, Filstroff, Louis, Sundin, Iiris, Kylmäoja, Juuso, Mikkola, Petrus   +5 more
core   +1 more source

TinyML Security: Exploring Vulnerabilities in Resource-Constrained Machine Learning Systems

Tiny Machine Learning (TinyML) systems, which enable machine learning inference on highly resource-constrained devices, are transforming edge computing but encounter unique security challenges. These devices, restricted by RAM and CPU capabilities two to
Beerel, Peter A., Huckelberry, Jacob, Zhang, Yuke, Mickens, James, Sansone, Allison, Reddi, Vijay Janapa   +5 more
core  

Thin fabric pressure sensors and TinyML smart gloves for edge IoT. [PDF]

iScience
Nguyen TN, Vu CC, Nguyen VH, Phan VC.
europepmc   +1 more source

Cyber resilience across domains: an in-depth exploration of cybersecurity practices and paradigms from the home environment to Operational Technology (OT). [PDF]

Sci Rep
Sakthivel T, Balasubramanian K.
europepmc   +1 more source

Real-Time Cardiac Arrhythmia Classification Using TinyML on Ultra-Low-Cost Microcontrollers: A Feasibility Study for Resource-Constrained Environments. [PDF]

Bioengineering (Basel)
Zambrano-de la Torre M, Guzman-Alfaro S, Acuña-Correa A, Soto-Murillo MA, Guzmán-Fernández M, Robles-Ortiz R, Villagrana-Bañuelos KE, Arceo-Olague JG, Espino-Salinas CH, Sánchez-Reyna AG, Cuevas-Rodriguez EO.   +10 more
europepmc   +1 more source

A Sensor-Based TinyML Acoustic Monitoring System for Edge-Side Animal Sound Recognition on Resource-Constrained Microcontrollers. [PDF]

Sensors (Basel)
Wang Z, Yu G.
europepmc   +1 more source