Convergence of edge computing and deep learning: A comprehensive survey

X Wang, Y Han, VCM Leung, D Niyato… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

A lightweight CNN model for detecting respiratory diseases from lung auscultation sounds using EMD-CWT-based hybrid scalogram

SB Shuvo, SN Ali, SI Swapnil, T Hasan… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Listening to lung sounds through auscultation is vital in examining the respiratory system for
abnormalities. Automated analysis of lung auscultation sounds can be beneficial to the …

Unsupervised human detection with an embedded vision system on a fully autonomous UAV for search and rescue operations

E Lygouras, N Santavas, A Taitzoglou, K Tarchanidis… - Sensors, 2019 - mdpi.com
Unmanned aerial vehicles (UAVs) play a primary role in a plethora of technical and scientific
fields owing to their wide range of applications. In particular, the provision of emergency …

CardioXNet: A novel lightweight deep learning framework for cardiovascular disease classification using heart sound recordings

SB Shuvo, SN Ali, SI Swapnil, MS Al-Rakhami… - ieee …, 2021 - ieeexplore.ieee.org
The alarmingly high mortality rate and increasing global prevalence of cardiovascular
diseases (CVDs) signify the crucial need for early detection schemes. Phonocardiogram …

Real time object detection and trackingsystem for video surveillance system

S Jha, C Seo, E Yang, GP Joshi - Multimedia Tools and Applications, 2021 - Springer
This paper introduces a system capable of real-time video surveillance in low-end edge
computing environment by combining object detection tracking algorithm. Recently, the …

Deep learning architectures in emerging cloud computing architectures: Recent development, challenges and next research trend

F Jauro, H Chiroma, AY Gital, M Almutairi… - Applied Soft …, 2020 - Elsevier
The challenges of the conventional cloud computing paradigms motivated the emergence of
the next generation cloud computing architectures. The emerging cloud computing …

Deep learning at the mobile edge: Opportunities for 5G networks

M McClellan, C Cervelló-Pastor, S Sallent - Applied Sciences, 2020 - mdpi.com
Mobile edge computing (MEC) within 5G networks brings the power of cloud computing,
storage, and analysis closer to the end user. The increased speeds and reduced delay …

Edge computing and its role in Industrial Internet: Methodologies, applications, and future directions

T Zhang, Y Li, CLP Chen - Information Sciences, 2021 - Elsevier
Abstract Proliferation of Industrial Internet has dramatically changed the way we live and
work. It brings convenience to our society and sometimes requires real-time processing of …

A microservice-enabled architecture for smart surveillance using blockchain technology

D Nagothu, R Xu, SY Nikouei… - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
While the smart surveillance system enhanced by the Internet of Things (IoT) technology
becomes an essential part of Smart Cities, it also brings new concerns in security of the data …

Blendmas: A blockchain-enabled decentralized microservices architecture for smart public safety

R Xu, SY Nikouei, Y Chen, E Blasch… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Thanks to rapid technological advances in the Internet of Things (IoT), a smart public safety
(SPS) system has become feasible by integrating heterogeneous computing devices to …