Results 31 to 40 of about 374 (124)

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

Leveraging Lightweight AI for Anomaly Detection in Mechanical Power Transmission At The Edge [PDF]

EPJ Web of Conferences
The integration of IoT and TinyML platforms has revolutionized fault detection and condition monitoring in electromechanical systems, enabling real-time data acquisition and analysis in resource-constrained environments.
Ayadi Walid, Amouri Amar, Ali Saeed, Alzahmi Nada, Khalid Mohammad Nadeem   +4 more
doaj   +1 more source

Physical Reservoir Computing for Smart Manufacturing of PCB Using Crystallinity‐Controlled HfO2 Memristor for Reservoir

Advanced Intelligent Systems, Volume 8, Issue 4, April 2026.
We address multilayer PCB anomaly detection for smart manufacturing by physical reservoir computing with HfO2‐based memristors. Crystallinity‐tuned HfO2 suppresses ferroelectricity while preserving the high‐k insulating state and confers strong short‐term memory.
Yongho Lee, Wonhee Lee, Junho Shin, Noah Jang, Hyunjun Kim, Da Ye Kim, Jinkyung Kim, June Soo Kim   +7 more
wiley   +1 more source

OBJECT DETECTION ALGORITHMS IMPLEMENTATION ON EMBEDDED DEVICES: CHALLENGES AND SUGGESTED SOLUTIONS

Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ
Object detection and image classification are among the most important areas to which scientific research is directed, which are commonly used in various applications based on computer vision.
Ruqaya Alaa, Ehab Hussein, Hilal Al-libawy   +2 more
doaj   +1 more source

CMOS-MEMS Gas Sensor Dubbed GMOS for SelectiveAnalysis of Gases with Tiny Edge Machine Learning

Engineering Proceedings, 2022
Embedded machine learning, TinyML, is a relatively new and fast-growing field of ML, enabling on-device sensor data analytics at low power requirements. This paper presents possible improvements to GMOS, a gas sensor, using TinyML technology.
Adir Krayden, Maayan Schohet, Oz Shmueli, Dima Shlenkevitch, Tanya Blank, Sara Stolyarova, Yael Nemirovsky   +6 more
doaj   +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

An Overview of Deep Learning Techniques for Big Data IoT Applications

International Journal of Communication Systems, Volume 39, Issue 4, 10 March 2026.
Reviews deep learning integration with cloud, fog, and edge computing in IoT architectures. Examines model suitability across IoT applications, key challenges, and emerging trends Provides a comparative analysis to guide future deep learning research in IoT environments.
Gagandeep Kaur, Vipin Balyan, Sindhu Hak Gupta   +2 more
wiley   +1 more source

Unlocking Edge Intelligence Through Tiny Machine Learning (TinyML)

IEEE Access, 2022
Machine Learning (ML) on the edge is key to enabling a new breed of IoT and autonomous system applications. The departure from the traditional cloud-centric architecture means that new deployments can be more power-efficient, provide better privacy and ...
Syed Ali Raza Zaidi, Ali M. Hayajneh, Maryam Hafeez, Q. Z. Ahmed   +3 more
doaj   +1 more source

Datasheets for machine learning sensors

AI Magazine, Volume 47, Issue 1, Spring 2026.
Abstract Machine learning (ML) is becoming prevalent in embedded AI sensing systems. These “ML sensors” enable context‐sensitive, real‐time data collection and decision‐making across diverse applications ranging from anomaly detection in industrial settings to wildlife tracking for conservation efforts.
Matthew Stewart, Yuke Zhang, Pete Warden, Yasmine Omri, Shvetank Prakash, Jacob Huckelberry, Joao Henrique Santos, Shawn Hymel, Benjamin Yeager Brown, Jim MacArthur, Nat Jeffries, Emanuel Moss, Mona Sloane, Brian Plancher, Vijay Janapa Reddi   +14 more
wiley   +1 more source

Next‐Generation Wearable Optical Sensors for Personalized Health and Point‐of‐Care Diagnostics—A Systematic Review

Advanced Healthcare Materials, Volume 15, Issue 10, 13 March 2026.
This review article presents a comprehensive and integrated overview of wearable optical sensors, systematically bridging advanced functional materials with fundamental optical sensing mechanisms. It further highlights their diverse applications across healthcare, fitness monitoring, environmental surveillance, and food safety.
Rituparna Duarah, Helena Torné‐Morató, Guolong Zhang, Youssef Amin, Mahdieh Pabast, Nidhi Sharma, Sailing He, Manash R. Das, Pier Paolo Pompa   +8 more
wiley   +1 more source