Large language models empowered autonomous edge AI for connected intelligence

Y Shen, J Shao, X Zhang, Z Lin, H Pan… - IEEE …, 2024 - ieeexplore.ieee.org
The evolution of wireless networks gravitates towards connected intelligence, a concept that
envisions seamless interconnectivity among humans, objects, and intelligence in a hyper …

Energy-sustainable iot connectivity: Vision, technological enablers, challenges, and future directions

OLA López, OM Rosabal… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Technology solutions must effectively balance economic growth, social equity, and
environmental integrity to achieve a sustainable society. Notably, although the Internet of …

Noninvasive diabetes detection through human breath using TinyML-Powered E-Nose

A Gudiño-Ochoa, JA García-Rodríguez… - Sensors, 2024 - mdpi.com
Volatile organic compounds (VOCs) in exhaled human breath serve as pivotal biomarkers
for disease identification and medical diagnostics. In the context of diabetes mellitus, the …

On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Case

F Dehrouyeh, L Yang, FB Ajaei, A Shami - arXiv preprint arXiv:2404.16894, 2024 - arxiv.org
As technology advances, the use of Machine Learning (ML) in cybersecurity is becoming
increasingly crucial to tackle the growing complexity of cyber threats. While traditional ML …

Towards AI-enabled Cloud Continuum for IIoT: Challenges and Opportunities

E Rojas, D Carrascal, D Lopez-Pajares… - … , Data Sciences and …, 2024 - ieeexplore.ieee.org
The last decade has demonstrated an exponential growth in connected devices, particularly
at the network edge, and this marked tendency still foresees a increase of the number of …

Learn From Others and Be Yourself in Federated Human Activity Recognition via Attention-Based Pairwise Collaborations

C Bu, L Zhang, H Cui, D Cheng, H Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Federated learning has recently been an emerging learning paradigm for training deep
neural networks for activity recognition on resource-limited portable devices such as …

Tiny machine learning empowers climbing inspection robots for real-time multiobject bolt-defect detection

TH Lin, CT Chang, A Putranto - Engineering Applications of Artificial …, 2024 - Elsevier
Ensuring the structural integrity of steel construction is critical, necessitating effective
methods for detecting bolt defects. Traditional inspection methods are reliable but require …

[HTML][HTML] Attention-Driven Transfer Learning Model for Improved IoT Intrusion Detection

S Abdelhamid, I Hegazy, M Aref… - Big Data and Cognitive …, 2024 - mdpi.com
The proliferation of Internet of Things (IoT) devices has become inevitable in contemporary
life, significantly affecting myriad applications. Nevertheless, the pervasive use of …

Tiny machine learning for underwater image enhancement: pruning and quantization approach

AA El Rejal, A Pester, K Nagaty - … International Conference on …, 2023 - ieeexplore.ieee.org
Many people have expressed an interest in underwater image processing in a variety of
fields, including underwater vehicle control, archaeology, marine biological studies, etc …

Semantic Meta-Split Learning: A TinyML Scheme for Few-Shot Wireless Image Classification

E Eldeeb, M Shehab, H Alves, MS Alouini - arXiv preprint arXiv …, 2024 - arxiv.org
Semantic and goal-oriented (SGO) communication is an emerging technology that only
transmits significant information for a given task. Semantic communication encounters many …