3.9 KiB
- Mdnotes File Name: trakadasArtificialIntelligenceBasedCollaboration2020
Gray Annotations (18/12/2020, 15:08:12)
"Industry 4.0 concepts are expected to significantly increase their footprint in industrial sectors by 20% in the next five years, since they allow leaner and more ecient production [4,5]" (Trakadas et al 2020:5481)
"In this context, many manufacturing companies are interested in accelerating the adoption and integration of secure, trustworthy artificial intelligence (AI) [6]" (Trakadas et al 2020:5481)
"AI-based manufacturing has the potential to improve the business key performance indicators (KPIs) of manufacturing processes by leveraging heterogeneous industrial big data analysis, information modelling and federation [7-9]" (Trakadas et al 2020:5481)
"interconnection of AI-based manufacturing processes with currently deployed wireless networks is a challenging research field, especially when central processing is performed outside industrial premises [10,11]" (Trakadas et al 2020:5481)
"AI is critical to the cybersecurity aspect of an IIoT-enabled connected manufacturing environment, for accurately detecting and mitigating threats [16-19]" (Trakadas et al 2020:5481)
"Industry 4.0 will make machines increasingly smarter by using AI models [28]" (Trakadas et al 2020:5482)
REFERENCE IMPORTANTE CHE MOTIVA ASPETTI DI INTEROPERABILITA' (note on p.5483)
"TensorFlow Federated provide support for decentralized AI models learning or computation over locally controlled data sources [39]." (Trakadas et al 2020:5486)
"adopting this novel approach [40], this scheme heavily reduces the administrative eort for key sharing and management, while ensuring end-to-end information protection" (Trakadas et al 2020:5487)
"adversarial attacks, which is the core element of trustworthy AI, has recently received much attention [41]." (Trakadas et al 2020:5487)
"The creation of models of the state and behavior can be done in a semi-automatic manner, using a newly devised AutoML tool that takes as input vector representations of sequential input data [46]" (Trakadas et al 2020:5488)
AUTOML (note on p.5488)
"Currently, federated learning is being adopted in dierent scenarios such as banking [61] and healthcare [62]." (Trakadas et al 2020:5490)
HERE WE HAVE COUPLE OF CONCRETE SCNEARIOS USING FEDERATED LEARNING (note on p.5490)
"There are currently many research activities to develop faster or more resource ecient PSI protocols [38,64]." (Trakadas et al 2020:5490)
"26. Sittón-Candanedo, I.; Alonso, R.C.; Rodríguez-González, S.; Alberto García Coria, J.; De La Prieta, F. Edge Computing Architectures in Industry 4.0: A General Survey and Comparison. In International Workshop on Soft Computing Models in Industrial and Environmental Applications; Springer: Cham, Switzerland, 2019; Volume 950." (Trakadas et al 2020:5497)
"Comiter, M. Attacking Artificial Intelligence, AI's Security Vulnerability and What Policymakers about It. In Belfer Center Paper; Harvard Kenedy School: Cambridge, MA, USA, 2019." (Trakadas et al 2020:5498)