Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications

RA Khalil, N Saeed, M Masood, YM Fard… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …

FormerLeaf: An efficient vision transformer for Cassava Leaf Disease detection

HT Thai, KH Le, NLT Nguyen - Computers and Electronics in Agriculture, 2023 - Elsevier
Leaf diseases have become more prevalent in recent years due to climate change,
increased growth of outdoor air pollutants, and global warming. They may severely damage …

Cloud–edge microservices architecture and service orchestration: An integral solution for a real-world deployment experience

L Roda-Sanchez, C Garrido-Hidalgo, F Royo… - Internet of Things, 2023 - Elsevier
After some years in which information management has been centralized in cloud platforms,
the need to implement architectures that perform more efficient and intelligent management …

Cloud versus edge deployment strategies of real-time face recognition inference

A Koubaa, A Ammar, A Kanhouch… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Choosing the appropriate deployment strategy for any Deep Learning (DL) project in a
production environment has always been the most challenging problem for industrial …

A lightweight CNN-based model for early warning in sow oestrus sound monitoring

Y Wang, S Li, H Zhang, T Liu - Ecological Informatics, 2022 - Elsevier
The reproductive performance of sows is an important indicator for evaluating the economic
efficiency and production level of pigs. In this paper, we design and propose a lightweight …

Edge deployment framework of guardbot for optimized face mask recognition with real-time inference using deep learning

S Manzoor, EJ Kim, SH Joo, SH Bae, GG In… - Ieee …, 2022 - ieeexplore.ieee.org
Deep learning based models on the edge devices have received considerable attention as
a promising means to handle a variety of AI applications. However, deploying the deep …

[HTML][HTML] Architecture for enabling edge inference via model transfer from cloud domain in a kubernetes environment

P Pääkkönen, D Pakkala, J Kiljander, R Sarala - Future Internet, 2020 - mdpi.com
The current approaches for energy consumption optimisation in buildings are mainly
reactive or focus on scheduling of daily/weekly operation modes in heating. Machine …

Towards an attention-based threat detection system for iot networks

TN Nguyen, KM Dang, AD Tran, KH Le - International Conference on …, 2022 - Springer
The proliferation of the Internet of Things (IoT) serves demands in our life ranging from smart
homes and smart cities to manufacturing and many other industries. As a result of the …

Towards smart traffic lights based on deep learning and traffic flow information

NY Tran-Van, XH Nguyerr, KH Le - 2022 9th NAFOSTED …, 2022 - ieeexplore.ieee.org
Traffic congestion is a significant cause hindering development and adversely affecting
socio-economic life; mean-while, traditional traffic light systems have become obsolete …

An Edge-based Fire Detection System for Real-Time IoT Applications

HT Thai, NY Tran-Van, KH Le-Minh… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Fire detection is a crucial research topic that has recently attracted many works. However,
most of these existing methods tend to achieve high accuracy based on large deep neural …