Results 21 to 30 of about 374 (124)

An autonomous network of acoustic detectors to map tiger risk by eavesdropping on prey alarm calls

Remote Sensing in Ecology and Conservation, EarlyView.
Tiger population recovery brings with it increased fatalities from human‐tiger conflict. We describe a network of autonomous intelligent passive acoustic sensors that monitor the forest for deer alarm calls as a proxy for tiger risk and provide a risk map to local communities in real‐time.
Arik Kershenbaum, Andrew Markham, Holly Root‐Gutteridge, Bethany Smith, Casey Anderson, Riley McClaughry, Ramjan Chaudhary, Amogh Vishwakarma, Stephen Cummins, Angela Dassow   +9 more
wiley   +1 more source

Tiny Machine Learning (TinyML): Research trends and future application opportunities

Array
Tiny Machine Learning (TinyML) enables artificial intelligence on low-power edge devices, yet a quantitative understanding of TinyML research remains limited.
Hui Han, Silvana Trimi, Sang M. Lee
doaj   +1 more source

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

Trends and Challenges in AIoT/IIoT/IoT Implementation

Sensors, 2023
For the next coming years, metaverse, digital twin and autonomous vehicle applications are the leading technologies for many complex applications hitherto inaccessible such as health and life sciences, smart home, smart agriculture, smart city, smart car
Kun Mean Hou, Xunxing Diao, Hongling Shi, Hao Ding, Haiying Zhou, Christophe de Vaulx   +5 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

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

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

Tiny Machine Learning and On-Device Inference: A Survey of Applications, Challenges, and Future Directions

Sensors
The growth in artificial intelligence and its applications has led to increased data processing and inference requirements. Traditional cloud-based inference solutions are often used but may prove inadequate for applications requiring near-instantaneous ...
Soroush Heydari, Qusay H. Mahmoud
doaj   +1 more source