Results 51 to 60 of about 374 (124)

Multimodal AI for Real‐Time Food Safety and Quality: From Sensors to Foundation Models, Edge Deployment, and Regulation

Food Science &Nutrition, Volume 14, Issue 2, February 2026.
The graphical abstract depicts an integrated multimodal AI pipeline for real‐time food safety and quality across the farm‐to‐fork continuum, where heterogeneous sensing modalities including vision, spectroscopy, electronic nose volatiles, biosensing, and IoT/RFID generate complementary data streams that undergo dataset engineering through ...
Zhaojie Chen, Guangyu Zhang, Fan Zhang
wiley   +1 more source

Towards scalable insect monitoring: Ultra‐lightweight CNNs as on‐device triggers for insect camera traps

Methods in Ecology and Evolution, Volume 17, Issue 2, Page 357-370, February 2026.
Abstract Camera traps, combined with AI, have emerged to achieve automated, scalable biodiversity monitoring. However, passive infrared (PIR) sensors that typically trigger camera traps are poorly suited for detecting small, fast‐moving ectotherms such as insects. Insects comprise over half of all animal species and are key components of ecosystems and
Ross J. Gardiner, Sareh Rowlands, Benno I. Simmons   +2 more
wiley   +1 more source

A Joint Survey in Decentralized Federated Learning and TinyML: A Brief Introduction to Swarm Learning

Future Internet
TinyML/DL is a new subfield of ML that allows for the deployment of ML algorithms on low-power devices to process their own data. The lack of resources restricts the aforementioned devices to running only inference tasks (static TinyML), while training ...
Evangelia Fragkou, Dimitrios Katsaros
doaj   +1 more source

Microfabricated Neural Biosensors for Detection of Neurotransmitters, Biomarkers, and Small Molecules: Emerging Trends on Self‐Sustained Systems and Energy Harvesting

Advanced Sensor Research, Volume 5, Issue 1, January 2026.
This paper reviews the state of the art and recent developments in thin‐film biosensors for the detection of neurotransmitters, small molecules, and biomarkers within flexible, implantable bioelectronic systems. It covers the main sensing modalities, including electrochemical, plasmonic, acoustic, and magnetic, alongside their materials, transduction ...
Massimo Mariello
wiley   +1 more source

A Review on Resource-Constrained Embedded Vision Systems-Based Tiny Machine Learning for Robotic Applications

Algorithms
The evolution of low-cost embedded systems is growing exponentially; likewise, their use in robotics applications aims to achieve critical task execution by implementing sophisticated control and computer vision algorithms. We review the state-of-the-art
Miguel Beltrán-Escobar, Teresa E. Alarcón, Jesse Y. Rumbo-Morales, Sonia López, Gerardo Ortiz-Torres, Felipe D. J. Sorcia-Vázquez   +5 more
doaj   +1 more source

From Detection to Countermeasure: A Review of Key Technologies in Counter‐Unmanned Aerial Vehicle Systems

IET Cyber-Systems and Robotics, Volume 8, Issue 1, January/December 2026.
ABSTRACT With the rapid proliferation of unmanned aerial vehicles (UAVs) in the military, logistics and public safety sectors, the threat of illegal intrusion, information theft, and security breaches has increased. This paper provides a comprehensive review of recent developments in counter‐unmanned aerial vehicle (counter‐UAV) systems, focussing on ...
Lei Xing, Can Cui, Miao Wang, Chao Xu
wiley   +1 more source

TinyML-Based Swine Vocalization Pattern Recognition for Enhancing Animal Welfare in Embedded Systems

Inventions
The automatic recognition of animal vocalizations is a valuable tool for monitoring pigs’ behavior, health, and welfare. This study investigates the feasibility of implementing a convolutional neural network (CNN) model for classifying pig vocalizations ...
Tung Chiun Wen, Caroline Ferreira Freire, Luana Maria Benicio, Giselle Borges de Moura, Magno do Nascimento Amorim, Késia Oliveira da Silva-Miranda   +5 more
doaj   +1 more source

High Accuracy of Epileptic Seizure Detection Using Tiny Machine Learning Technology for Implantable Closed-Loop Neurostimulation Systems

BioMedInformatics
Background: Epilepsy is one of the most common and devastating neurological disorders, manifesting with seizures and affecting approximately 1–2% of the world’s population.
Evangelia Tsakanika, Vasileios Tsoukas, Athanasios Kakarountas, Vasileios Kokkinos   +3 more
doaj   +1 more source

Reliable ECG Anomaly Detection on Edge Devices for Internet of Medical Things Applications

Sensors
The advent of Tiny Machine Learning (TinyML) has unlocked the potential to deploy machine learning models on resource-constrained edge devices, revolutionizing real-time monitoring in Internet of Medical Things (IoMT) applications.
Moez Hizem, Leila Bousbia, Yassmine Ben Dhiab, Mohamed Ould-Elhassen Aoueileyine, Ridha Bouallegue   +4 more
doaj   +1 more source

Voice-activated home automation system for IoT edge devices using TinyML

Discover Internet of Things
Home automation systems are popular because they enhance the quality of life and the way users interact with the environment. Deploying complex machine learning models on Internet of Things (IoT) devices with limited resources is still difficult.
Timothy Malche, Sandeep Budhani, Pramod Kumar Soni, Govind Murari Upadhyay   +3 more
doaj   +1 more source