Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities

Z Jan, F Ahamed, W Mayer, N Patel… - Expert Systems with …, 2023 - Elsevier
Many industry sectors have been pursuing the adoption of Industry 4.0 (I4. 0) ideas and
technologies, which promise to realize lean and just-in-time production through digitization …

Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the …

T Ahmad, R Madonski, D Zhang, C Huang… - … and Sustainable Energy …, 2022 - Elsevier
The current trend indicates that energy demand and supply will eventually be controlled by
autonomous software that optimizes decision-making and energy distribution operations …

[HTML][HTML] Deep learning modelling techniques: current progress, applications, advantages, and challenges

SF Ahmed, MSB Alam, M Hassan, MR Rozbu… - Artificial Intelligence …, 2023 - Springer
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

Applications of smart technologies in logistics and transport: A review

SH Chung - Transportation Research Part E: Logistics and …, 2021 - Elsevier
The emergence of smart technologies (STs) is inducing significant transformation in logistics
and transport nowadays. STs refer to the applications of artificial intelligence and data …

Machine learning-powered encrypted network traffic analysis: A comprehensive survey

M Shen, K Ye, X Liu, L Zhu, J Kang… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …

[HTML][HTML] Artificial intelligence-based cyber security in the context of industry 4.0—a survey

AJG De Azambuja, C Plesker, K Schützer, R Anderl… - Electronics, 2023 - mdpi.com
The increase in cyber-attacks impacts the performance of organizations in the industrial
sector, exploiting the vulnerabilities of networked machines. The increasing digitization and …

Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects

T Berghout, M Benbouzid, SM Muyeen - International Journal of Critical …, 2022 - Elsevier
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …

Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

F Ahsan, NH Dana, SK Sarker, L Li… - … and Control of …, 2023 - ieeexplore.ieee.org
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …

Sustainability in wood products: a new perspective for handling natural diversity

M Schubert, G Panzarasa, I Burgert - Chemical Reviews, 2022 - ACS Publications
Wood is a renewable resource with excellent qualities and the potential to become a key
element of a future bioeconomy. The increasing environmental awareness and drive to …

[HTML][HTML] Operationalizing Digitainability: Encouraging mindfulness to harness the power of digitalization for sustainable development

S Gupta, J Campos Zeballos, G del Río Castro… - Sustainability, 2023 - mdpi.com
Digitalization is globally transforming the world with profound implications. It has enormous
potential to foster progress toward sustainability. However, in its current form, digitalization …