Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives
The innovative technologies emerged with the industrial revolution “Industry 4.0” as well as
the new ones on the way of advanced digitalization enable delivering enhanced, value …
the new ones on the way of advanced digitalization enable delivering enhanced, value …
[HTML][HTML] The Internet of Things and the circular economy: A systematic literature review and research agenda
In recent years, the concept of a circular economy (CE) has gained importance and attracted
significant attention among scholars and practitioners. Research that examines the role of …
significant attention among scholars and practitioners. Research that examines the role of …
[HTML][HTML] Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries
Abstract Internet of Things (IoT) technology, which has made manufacturing processes more
smart, efficient and sustainable, has received increasing attention from the industry and …
smart, efficient and sustainable, has received increasing attention from the industry and …
Deep learning-assisted smart process planning, robotic wireless sensor networks, and geospatial big data management algorithms in the internet of manufacturing …
G Lăzăroiu, M Andronie, M Iatagan… - … International Journal of …, 2022 - mdpi.com
The purpose of our systematic review is to examine the recently published literature on the
Internet of Manufacturing Things (IoMT), and integrate the insights it configures on deep …
Internet of Manufacturing Things (IoMT), and integrate the insights it configures on deep …
[HTML][HTML] Big data-driven correlation analysis based on clustering for energy-intensive manufacturing industries
Abstract In Industry 4.0, the production data obtained from the Internet of Things has reached
the magnitude of big data with the emergence of advanced information and communication …
the magnitude of big data with the emergence of advanced information and communication …
Energy digitalization: Main categories, applications, merits, and barriers
Increased consumption of fossil fuels has contributed to a rise in abnormal weather
conditions. Utilizing renewable energy sources is one of the most effective methods for …
conditions. Utilizing renewable energy sources is one of the most effective methods for …
A comprehensive review of machine learning and IoT solutions for demand side energy management, conservation, and resilient operation
The energy consumption of major equipment in residential and industrial facilities can be
minimized through a variety of cost-effective energy-saving measures. Most saving …
minimized through a variety of cost-effective energy-saving measures. Most saving …
[HTML][HTML] Edge-cloud cooperation-driven smart and sustainable production for energy-intensive manufacturing industries
Energy-intensive manufacturing industries are characterised by high pollution and heavy
energy consumption, severely challenging the ecological environment. Fortunately …
energy consumption, severely challenging the ecological environment. Fortunately …
Attention mechanism-aided data-and knowledge-driven soft sensors for predicting blast furnace gas generation
S Liu, W Sun - Energy, 2023 - Elsevier
Blast furnace gas (BFG) is an important energy-carrying byproduct of the iron and steel
industry. High-accuracy prediction of BFG generation is the basis of the dynamic balance of …
industry. High-accuracy prediction of BFG generation is the basis of the dynamic balance of …
Unified whale optimization algorithm based multi-kernel SVR ensemble learning for wind speed forecasting
H Xian, J Che - Applied Soft Computing, 2022 - Elsevier
Support vector regression (SVR) is widely used in the field of wind speed forecasting
because of its excellent nonlinear learning ability. However, the drawback of SVR is the …
because of its excellent nonlinear learning ability. However, the drawback of SVR is the …