Applications, Modern Trends, and Challenges of Multiscale Modeling in Smart Cities

D Mondal, A Ratnaparkhi, A Deshpande… - … of Research on Data …, 2023 - igi-global.com
Megacities are intricate systems that struggle with difficulties including overcrowding, subpar
urban design and planning, inadequate mobility and public transportation, subpar …

[HTML][HTML] Framework for the strategic adoption of industry 4.0: a focus on intelligent systems

J Serey, M Alfaro, G Fuertes, M Vargas, R Ternero… - Processes, 2023 - mdpi.com
Despite growing interest in smart manufacturing, there is little information on how
organizations can approach the alignment of strategic processes with Industry 4.0. This …

[HTML][HTML] Predictive maintenance planning for industry 4.0 using machine learning for sustainable manufacturing

MH Abidi, MK Mohammed, H Alkhalefah - Sustainability, 2022 - mdpi.com
With the advent of the fourth industrial revolution, the application of artificial intelligence in
the manufacturing domain is becoming prevalent. Maintenance is one of the important …

Deep learning-based transfer learning for classification of skin cancer

S Jain, U Singhania, B Tripathy, EA Nasr, MK Aboudaif… - Sensors, 2021 - mdpi.com
One of the major health concerns for human society is skin cancer. When the pigments
producing skin color turn carcinogenic, this disease gets contracted. A skin cancer diagnosis …

[HTML][HTML] An integrated outlook of Cyber–Physical Systems for Industry 4.0: Topical practices, architecture, and applications

M Javaid, A Haleem, RP Singh, R Suman - Green Technologies and …, 2023 - Elsevier
Industry 4.0 requires a strong understanding of Cyber–Physical Systems (CPS). An Industry
4.0-enabled manufacturing environment that offers real-time data gathering, transparency …

Construction of sustainable digital factory for automated warehouse based on integration of ERP and WMS

Q Tong, X Ming, X Zhang - Sustainability, 2023 - mdpi.com
The integration and application of a warehouse system and manufacturing system has
become a manufacturing problem for enterprises. The main reason is that the information …

Edge intelligence and agnostic robotic paradigm in resource synchronisation and sharing in flexible robotic and facility control system

KL Keung, YY Chan, KKH Ng, SL Mak, CH Li… - Advanced Engineering …, 2022 - Elsevier
The agnostic robotic paradigm (ARP) represents a recent development as the use of robots
becomes more common, and there is a need for agnostic robots to cope with rich artificial …

Big data-based smart health monitoring system: using deep ensemble learning

MH Abidi, U Umer, SH Mian, A Al-Ahmari - IEEE Access, 2023 - ieeexplore.ieee.org
Human life has become smarter by utilizing big data, telecommunication technologies, and
wearable sensors over pervasive computing to give better healthcare services. Big data is …

[HTML][HTML] Federated split learning model for industry 5.0: A data poisoning defense for edge computing

F Khan, RL Kumar, MH Abidi, S Kadry, H Alkhalefah… - Electronics, 2022 - mdpi.com
Industry 5.0 provides resource-efficient solutions compared to Industry 4.0. Edge Computing
(EC) allows data analysis on edge devices. Artificial intelligence (AI) has become the focus …

Annealing of monel 400 alloy using principal component analysis, hyper-parameter optimization, machine learning techniques, and multi-objective particle swarm …

S Chintakindi, A Alsamhan, MH Abidi… - International Journal of …, 2022 - Springer
The purpose of this paper is to investigate the effect of the annealing process at 1000° C on
machining parameters using contemporary techniques such as principal component …