Systematic review on machine learning (ML) methods for manufacturing processes–Identifying artificial intelligence (AI) methods for field application
S Fahle, C Prinz, B Kuhlenkötter - Procedia CIRP, 2020 - Elsevier
Artificial Intelligence (AI) and especially machine learning (ML) become increasingly more
frequently applicable in factory operations. This paper presents a systematic review of …
frequently applicable in factory operations. This paper presents a systematic review of …
Industry 4.0 disruption and its neologisms in major industrial sectors: A state of the art
Very well into the dawn of the fourth industrial revolution (industry 4.0), humankind can
hardly distinguish between what is artificial and what is natural (eg, man‐made virus and …
hardly distinguish between what is artificial and what is natural (eg, man‐made virus and …
IoT in smart cities: A survey of technologies, practices and challenges
AS Syed, D Sierra-Sosa, A Kumar, A Elmaghraby - Smart Cities, 2021 - mdpi.com
Internet of Things (IoT) is a system that integrates different devices and technologies,
removing the necessity of human intervention. This enables the capacity of having smart (or …
removing the necessity of human intervention. This enables the capacity of having smart (or …
Detection and prediction of fdi attacks in iot systems via hidden markov model
False data injection (FDI) attacks aim to threaten the security of Internet of Things (IoT)
systems by falsifying a device's measurements without being detected. In this paper, we …
systems by falsifying a device's measurements without being detected. In this paper, we …
Cloud-based industrial cyber–physical system for data-driven reasoning: A review and use case on an industry 4.0 pilot line
Nowadays, reconfiguration and adaptation by means of optimal re-parameterization in
Industrial Cyber-Physical Systems (ICPSs) is one of the bottlenecks for the digital …
Industrial Cyber-Physical Systems (ICPSs) is one of the bottlenecks for the digital …
A systematic literature review on distributed machine learning in edge computing
CP Filho, E Marques Jr, V Chang, L Dos Santos… - Sensors, 2022 - mdpi.com
Distributed edge intelligence is a disruptive research area that enables the execution of
machine learning and deep learning (ML/DL) algorithms close to where data are generated …
machine learning and deep learning (ML/DL) algorithms close to where data are generated …
Business analytics in Industry 4.0: A systematic review
Abstract Recently, the term “Industry 4.0” has emerged to characterize several Information
Technology and Communication (ICT) adoptions in production processes (eg, Internet‐of …
Technology and Communication (ICT) adoptions in production processes (eg, Internet‐of …
An IoT-based deep learning approach to analyse indoor thermal comfort of disabled people
B Brik, M Esseghir, L Merghem-Boulahia… - Building and …, 2021 - Elsevier
Monitoring the thermal comfort of building occupants is crucial for ensuring sustainable and
efficient energy consumption in residential buildings. Existing studies have addressed the …
efficient energy consumption in residential buildings. Existing studies have addressed the …
Resiliency of smart manufacturing enterprises via information integration
Smart Manufacturing enterprises emerge as interconnected, geographically distributed, data
driven, and adaptive. While smartness is improved by the integration of information, this also …
driven, and adaptive. While smartness is improved by the integration of information, this also …
Analysing the drivers for adoption of Industry 4.0 technologies in a functional paper–cement–sugar circular sharing network
KEK Vimal, K Churi, J Kandasamy - Sustainable Production and …, 2022 - Elsevier
Recent studies have established the relevance and importance of Industry 4.0 (I4. 0)
technologies in circular economy (CE) models. However, due to the vast contrast between …
technologies in circular economy (CE) models. However, due to the vast contrast between …