Real-time monitoring and diagnosis of a train door mechatronic system

2014 ◽  
Author(s):  
Laurent Cauffriez ◽  
Sebastien Grondel
Keyword(s):  
Real Time ◽  
Real Time Monitoring ◽  
Mechatronic System ◽  
Monitoring And Diagnosis

scholarly journals Real-Time Monitoring and Diagnosis Platform for a Machining Process

2008 ◽  
Vol 41 (2) ◽  
pp. 10674-10679
Author(s):  
E. Portillo ◽  
M. Marcos ◽  
I. Cabanes ◽  
D. Orive ◽  
J.A. Sánchez
Keyword(s):  
Real Time ◽  
Machining Process ◽  
Real Time Monitoring ◽  
Monitoring And Diagnosis

Design of a user-friendly LabVIEW-based toolbox for real-time monitoring and diagnosis of vital signals

2010 ◽  
Vol 2 (3) ◽  
pp. 307 ◽  
Author(s):  
Mashhour M. Bani Amer ◽  
Yasser Qtait ◽  
Lina Al Ebbini ◽  
Sammer Ammary ◽  
Maher Awwad
Keyword(s):  
Real Time ◽  
Real Time Monitoring ◽  
Monitoring And Diagnosis ◽  
User Friendly

Emphasizing privacy and security of edge intelligence with machine learning for healthcare

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sukumar Rajendran ◽  
Sandeep Kumar Mathivanan ◽  
Prabhu Jayagopal ◽  
Kumar Purushothaman Janaki ◽  
Benjula Anbu Malar Manickam Bernard ◽  
...  
Keyword(s):  
Real Time ◽  
Service Providers ◽  
Mobile Apps ◽  
Wearable Devices ◽  
Edge Computing ◽  
Processing Unit ◽  
Real Time Monitoring ◽  
Content Type ◽  
Monitoring And Diagnosis ◽  
The Impact

PurposeArtificial Intelligence (AI) has surpassed expectations in opening up different possibilities for machines from different walks of life. Cloud service providers are pushing. Edge computing reduces latency, improving availability and saving bandwidth.Design/methodology/approachThe exponential growth in tensor processing unit (TPU) and graphics processing unit (GPU) combined with different types of sensors has enabled the pairing of medical technology with deep learning in providing the best patient care. A significant role of pushing and pulling data from the cloud, big data comes into play as velocity, veracity and volume of data with IoT assisting doctors in predicting the abnormalities and providing customized treatment based on the patient electronic health record (EHR).FindingsThe primary focus of edge computing is decentralizing and bringing intelligent IoT devices to provide real-time computing at the point of presence (PoP). The impact of the PoP in healthcare gains importance as wearable devices and mobile apps are entrusted with real-time monitoring and diagnosis of patients. The impact edge computing of the PoP in healthcare gains significance as wearable devices and mobile apps are entrusted with real-time monitoring and diagnosis of patients.Originality/valueThe utility value of sensors data improves through the Laplacian mechanism of preserved PII response to each query from the ODL. The scalability is at 50% with respect to the sensitivity and preservation of the PII values in the local ODL.

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